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  • The Effect of Music Playlists on Streaming Services: Listener Retention and New Music Discovery

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    Introduction

    The rise of music streaming services has fundamentally altered how individuals consume and discover music. This transformation is largely driven by the ubiquitous nature of curated playlists, both algorithmically generated and human-curated. This analysis explores the multifaceted impact of music playlists on listener retention and the discovery of new music within streaming services, drawing upon a diverse range of research. The studies examined utilize various methodologies, including experiments, surveys, and analyses of streaming data, providing a comprehensive, albeit nuanced, understanding of the topic.

    The Role of Algorithmic Playlists

    Algorithmic playlists, such as Spotify’s Discover Weekly (Derwinis, NaN), (Janice, 2024), (Cole, 2024), represent a significant innovation in music recommendation. These playlists leverage user listening history and data-driven insights to generate personalized recommendations (Derwinis, NaN). However, the effectiveness of these algorithms in fostering listener retention and facilitating new music discovery is a subject of ongoing debate. While some research suggests that algorithmic playlists can successfully introduce users to diverse and relevant music (Lindsay, 2016), others highlight concerns about filter bubbles and echo chambers, where algorithms may reinforce existing preferences rather than expanding musical horizons (Silber, NaN). The study by Katarzyna Derwinis and J. F. Goncalves (Derwinis, NaN) found no significant differences in self-reported use between heavy and light Spotify users. However, it revealed that users who perceived themselves as heavy users enjoyed more diverse content and appreciated algorithmic recommendations more than light users, suggesting that perceived usage may influence the effectiveness of algorithmic playlists. This highlights the importance of considering user perception alongside objective metrics when evaluating the impact of algorithmic curation. Furthermore, the study by Natasha Janice and Nurrani Kusumawati (Janice, 2024) found a significant positive impact of the quality-of-service experience through Discover Weekly on user satisfaction and loyalty to Spotify, directly linking algorithmic playlist quality to user retention.

    The effectiveness of algorithmic playlists in driving new music discovery is also influenced by factors beyond the algorithm itself. The subjective organization of songs and genres within a platform’s interface, misrepresentation of songs and artists within genre-based playlists, and the use of user actions (skips, likes, dislikes, etc.) as an assertion of preferences all present challenges (Silber, NaN). These challenges highlight the limitations of relying solely on algorithms for music discovery and underscore the need for a more holistic approach that considers the user experience and the broader context of music consumption. The ACM Recommender Systems Challenge 2018 (Schedl, NaN) further emphasizes the importance of developing sophisticated algorithms for automatic playlist continuation, highlighting the ongoing effort to improve the user experience and engagement through enhanced recommendation systems. This challenge, focused on predicting missing tracks in user-created playlists, directly addresses the problem of seamlessly integrating new music discoveries into established listening habits.

    Human Curation and its Impact

    In contrast to algorithmic playlists, human-curated playlists offer a different approach to music discovery and listener retention. These playlists are created by music experts or curators who leverage their knowledge and experience to select songs that fit a specific theme or mood (Lindsay, 2016), (Cole, 2024). Research suggests that human-curated playlists provide more consistent recommendations compared to algorithmic curation (Lindsay, 2016), potentially enhancing listener satisfaction and fostering a sense of trust in the platform’s recommendations. The study by C. Lindsay (Lindsay, 2016) found that while human-curated playlists offered more consistent recommendations, algorithmic curation was more effective for discovering new music. This suggests a complementary role for both human and algorithmic approaches in optimizing the user experience. Sebastian Cole and Jessica Yarin Robinson (Cole, 2024) further highlight the importance of human curation in their study of Christmas music playlists, demonstrating how even within a seemingly homogenous genre, users employ playlists as a form of self-expression and individuality, highlighting the interplay between algorithmic and human curation in shaping user experience. The “algotorial” process employed by Spotify (Cole, 2024), a blend of human and algorithmic curation, exemplifies this trend towards integrating both approaches to optimize recommendation effectiveness.

    However, the role of human curators is not without its limitations. Concerns exist regarding potential biases and commercial influences that could affect the diversity and representativeness of curated playlists (Silber, NaN), (Cole, 2024). The influence of major labels and the potential for underrepresentation of independent artists or specific genres remain critical considerations (Prey, 2020), (Prey, 2020). Moreover, the opaque nature of playlist curation processes can limit transparency and accountability, raising concerns about potential manipulation or favoritism (Silber, NaN). The research by Robert Prey, Marc Esteve Del Valle, and Leslie R. Zwerwer (Prey, 2020), (Prey, 2020) highlights the significant role of Spotify’s editorial capacity in shaping music discovery and consumption patterns. Their analysis of promotion patterns on Spotify’s Twitter account reveals how the platform’s corporate strategy influences which artists and songs receive prominence, potentially affecting listener retention by promoting certain tracks and artists over others. This underscores the need for greater transparency and a deeper understanding of the factors influencing playlist curation to ensure fairness and diversity.

    Playlists and Listener Retention

    The relationship between music playlists and listener retention is complex and multifaceted. While effective playlists can enhance user engagement and satisfaction (Janice, 2024), (Cole, 2024), several factors can influence their impact on listener retention. User satisfaction is strongly linked to the quality of the listening experience (Janice, 2024), which is influenced by various factors including the diversity and relevance of recommendations, the ease of navigation, and the overall design of the platform (Gabbolini, 2022). The study by Giovanni Gabbolini and Derek Bridge (Gabbolini, 2022) found that a “Greedy” algorithm generated more liked experiences than an “Optimal” algorithm, suggesting that the specific algorithm used can significantly impact user satisfaction. Key factors for user satisfaction included segue diversity and song arrangement familiarity, indicating that the structural aspects of playlist design are crucial for creating a positive listening experience. Furthermore, the study by Sean Nicolas Brggemann (Brggemann, NaN) highlights the significant role of playlist curators in influencing listener behavior and track demand, emphasizing that effective targeted marketing hinges on identifying the right playlists for promoting tracks. This underscores the importance of playlist curation in driving listener engagement and retention.

    However, the impact of playlists on listener retention is not solely determined by the quality of the playlists themselves. Other factors, such as the overall user experience, the availability of other features on the platform, and the listener’s personal preferences, also play a significant role (Walsh, 2024), (Datta, 2017). The research by M. Walsh (Walsh, 2024) explores the phenomenon of background music, demonstrating how streaming services enable users to integrate music into everyday activities, often treating it as background audio. This suggests that while playlists might contribute to overall music consumption, the level of focused engagement with individual tracks might be reduced, potentially affecting the depth of listener connection and retention. The study by Hannes Datta, George Knox, and Bart J. Bronnenberg (Datta, 2017) found that adoption of streaming services leads to increased quantity and diversity of music consumption, but the effects attenuate over time. This suggests that while playlists can initially drive increased engagement, maintaining long-term listener retention requires a more comprehensive strategy. The study also highlights that repeat listening decreases, but the best discoveries have higher rates. This points to the importance of introducing new and engaging music to listeners, suggesting that playlists serve a crucial role in fostering long-term engagement.

    Playlists and the Discovery of New Music

    Playlists serve as a powerful tool for facilitating the discovery of new music on streaming services. However, the effectiveness of playlists in this regard depends on various factors, including the type of playlist (algorithmic or human-curated), the diversity of the recommendations, and the listener’s existing musical preferences (Silber, NaN), (Lindsay, 2016), (Cole, 2024). The study by C. Lindsay (Lindsay, 2016) found that algorithmic curation is more effective for discovering new music than human curation, suggesting that algorithms can be more successful in introducing users to unfamiliar artists and genres. However, the potential for algorithmic biases and the limitations of relying solely on data-driven recommendations remain a crucial concern (Silber, NaN). The study by Lorenzo Porcaro, Emlia Gmez, and Carlos Castillo (Porcaro, 2023) demonstrates that diverse music recommendations can positively impact listeners’ attitudes towards unfamiliar genres, suggesting that playlists featuring a wide range of music can help listeners overcome pre-existing biases and discover new artists and genres.

    The introduction of new music through playlists is also influenced by contextual factors, such as the listener’s emotional state and the specific listening environment (Walsh, 2024), (Ycel, 2022). The research by M. Walsh (Walsh, 2024) highlights how streaming services enable users to integrate music into everyday activities, often as background audio, which may affect their engagement with new music and retention of previously enjoyed tracks. The study by A. Ycel (Ycel, 2022) shows that music preference is associated with emotional state, suggesting that playlists tailored to specific emotions could enhance the discovery and appreciation of new music. The integration of music into diverse everyday activities can expand the role of music beyond focused listening sessions, potentially leading to increased overall music consumption and exposure to diverse genres (Walsh, 2024). However, this increased exposure may also lead to a diminished appreciation for focused listening and silence (Walsh, 2024), potentially impacting the depth of engagement with individual tracks and artists.

    The effectiveness of playlists in fostering music discovery is also influenced by the design and presentation of the playlists themselves (Gabbolini, 2022), (Bree, NaN), (Park, 2022). The research by Giovanni Gabbolini and Derek Bridge (Gabbolini, 2022) highlights the importance of factors like segue diversity and song arrangement familiarity in enhancing user satisfaction, suggesting that careful consideration of playlist design can significantly impact the listener’s experience and ability to discover new music. Furthermore, the study by Lotte van Bree, Mark P. Graus, and B. Ferwerda (Bree, NaN) shows that personalized vocabulary in playlist titles significantly influences user decision-making, suggesting that carefully crafted playlist titles can enhance the appeal of playlists and encourage exploration of new music. The research by So Yeon Park and Blair Kaneshiro (Park, 2022) highlights the importance of considering user needs and desires when designing collaborative playlists, emphasizing that features facilitating communication and multiple collaborator editing can enhance user satisfaction and engagement. This further underscores the importance of considering user-centric design principles when creating playlists to optimize their effectiveness in driving music discovery.

    The Influence of Platform Strategies

    The strategies employed by music streaming platforms significantly impact how playlists influence listener retention and the discovery of new music. Platforms like Spotify actively shape user experience through algorithmic personalization, editorial curation, and targeted marketing (Prey, 2020), (Prey, 2020), (Pedersen, 2020). However, these strategies are not without their limitations and potential drawbacks. The research by Robert Prey, Marc Esteve Del Valle, and Leslie R. Zwerwer (Prey, 2020), (Prey, 2020) highlights the significant role of Spotify’s curated playlists in shaping music discovery and listener retention. Their analysis demonstrates how Spotify’s promotional strategies influence the exposure of major and independent labels, potentially creating a leveling effect in music exposure while simultaneously raising concerns about potential biases and the reinforcement of existing power structures within the music industry. The research by Rasmus Rex Pedersen (Pedersen, 2020) examines Spotify’s data-driven approach to music recommendations, emphasizing the interplay between editorial curation and algorithmic curation in enhancing user experience. This hybrid approach, while aiming for personalization and contextualization, also raises questions about potential biases and the prioritization of user engagement over other considerations. The study by J. Morris (Morris, 2020) further explores the optimization of music for streaming platforms, highlighting the concept of “phonographic effects” where artists adapt their music to be more playlist-friendly, potentially impacting the authenticity and diversity of music available to listeners. The research also touches on artificial play counts and musical spam, highlighting the complex interplay between platform incentives, artist strategies, and user experiences.

    The platform’s approach to playlist design and recommendation algorithms also influences user behavior and engagement. The study by Cristina Alaimo and Jannis Kallinikos (Alaimo, 2020) investigates the role of algorithms in categorizing music on platforms like Last.fm, highlighting how algorithmic categorization impacts listeners’ perception and interaction with music, potentially influencing retention and discovery. The research also discusses the transition from expert-driven categorization to algorithm-based systems, emphasizing how this shift affects user engagement with music. The study by Marc Bourreau, Franois Moreau, and Patrik Wikstrm (Bourreau, 2021) analyzes music charts data to assess cultural content changes due to digitization, highlighting a significant increase in diversity with the introduction of Spotify. This suggests that the platform’s design and algorithms can have a significant impact on the diversity of music available to listeners, potentially affecting their ability to discover new music and their overall engagement with the platform. The study by Anthony T. Pinter, Jacob M. Paul, Jessie J. Smith, and Jed R. Brubaker (Pinter, 2020) further emphasizes the interplay between algorithmic curation and expert reviews in shaping music discovery, highlighting the influence of platforms like Pitchfork on listener choices and the subsequent success of artists.

    Limitations and Future Research

    While this analysis provides a comprehensive overview of the effect of music playlists on listener retention and the discovery of new music, several limitations and areas for future research remain. Many studies focus on specific platforms or genres, limiting the generalizability of findings. The methodologies employed vary across studies, making direct comparisons challenging. Furthermore, the subjective nature of user experience and the complex interplay of factors influencing listener behavior make it difficult to isolate the precise impact of playlists.

    Future research should address these limitations by conducting larger-scale, cross-platform studies that incorporate diverse methodologies. More sophisticated analyses of streaming data are needed to better understand the complex relationships between playlist characteristics, user engagement, and retention. Qualitative research, such as in-depth interviews and focus groups, can provide valuable insights into user perceptions and experiences with playlists. Furthermore, research exploring the long-term impacts of playlist exposure on listener preferences and musical tastes is crucial. Investigating the ethical implications of algorithmic personalization and the potential for biases in playlist curation is also essential. Finally, studying the impact of collaborative playlists and the role of social interactions in shaping music discovery and retention warrants further attention.

    Music playlists have become an integral part of the music streaming experience, significantly impacting listener retention and the discovery of new music. Algorithmic playlists offer personalized recommendations, potentially exposing listeners to diverse genres and artists. However, concerns remain regarding filter bubbles and echo chambers. Human-curated playlists provide consistent recommendations but may be subject to biases and commercial influences. Effective playlists enhance user engagement and satisfaction, but factors like user experience, platform features, and listening contexts also play a crucial role in listener retention. The strategies employed by streaming platforms significantly influence how playlists shape music discovery and consumption patterns. Future research should address the limitations of existing studies and explore the multifaceted relationships between playlists, user behavior, and the evolving landscape of music streaming. A more holistic approach, integrating quantitative and qualitative methods, is needed to fully understand the complex interplay of factors influencing the impact of music playlists on listener engagement and the ongoing evolution of music discovery.

    References

    Alaimo, C. & Kallinikos, J. (2020). Managing by data: algorithmic categories and organizing. SAGE Publishing. https://doi.org/10.1177/0170840620934062

    Bourreau, M., Moreau, F., & Wikstrm, P. (2021). Does digitization lead to the homogenization of cultural content?. Wiley. https://doi.org/10.1111/ecin.13015

    Bree, L. V., Graus, M. P., & Ferwerda, B. (NaN). Framing theory on music streaming platforms: how vocabulary influences music playlist decision-making and expectations. None. https://doi.org/None

    Brggemann, S. N. (NaN). Effectiveness of targeted digital marketing. None. https://doi.org/10.3929/ETHZ-B-000476394

    Cole, S. & Robinson, J. Y. (2024). Curating christmas. M/C Journal. https://doi.org/10.5204/mcj.3125

    Datta, H., Knox, G., & Bronnenberg, B. J. (2017). Changing their tune: how consumers adoption of online streaming affects music consumption and discovery. Institute for Operations Research and the Management Sciences. https://doi.org/10.1287/mksc.2017.1051


    Derwinis, K. & Goncalves, J. F. (NaN). Do they discover weekly your taste?. None. https://doi.org/None

    Gabbolini, G. & Bridge, D. (2022). A user-centered investigation of personal music tours. None. https://doi.org/10.1145/3523227.3546776

    Janice, N. & Kusumawati, N. (2024). Harmonizing algorithms and user satisfaction: evaluating the impact of spotify”s discover weekly on customer loyalty. None. https://doi.org/10.58229/jims.v2i2.168

    Lindsay, C. (2016). An exploration into how the rise of curation within streaming services has impacted how music fans in the uk discover new music. None. https://doi.org/None

    Morris, J. (2020). Music platforms and the optimization of culture. Social Media + Society. https://doi.org/10.1177/2056305120940690

    Park, S. Y. & Kaneshiro, B. (2022). User perspectives on critical factors for collaborative playlists. Public Library of Science. https://doi.org/10.1371/journal.pone.0260750

    Pedersen, R. R. (2020). Datafication and the push for ubiquitous listening in music streaming. Society of Media Researchers In Denmark. https://doi.org/10.7146/mediekultur.v36i69.121216

    Pinter, A. T., Paul, J. M., Smith, J. J., & Brubaker, J. R. (2020). P4kxspotify: a dataset of pitchfork music reviews and spotify musical features. None. https://doi.org/10.1609/icwsm.v14i1.7355

    Porcaro, L., Gmez, E., & Castillo, C. (2023). Assessing the impact of music recommendation diversity on listeners: a longitudinal study. Association for Computing Machinery. https://doi.org/10.1145/3608487

    Prey, R., Valle, M. E. D., & Zwerwer, L. (2020). Platform pop: disentangling spotifys intermediary role in the music industry. Information, Communication & Society. https://doi.org/10.1080/1369118X.2020.1761859

    Schedl, M., Zamani, H., Chen, C., Deldjoo, Y., & Elahi, M. (NaN). Recsys challenge 2018 : automatic playlist continuation. None. https://doi.org/None

    Silber, J. (NaN). Music recommendation algorithms: discovering weekly or discovering weakly?. None. https://doi.org/10.33767/osf.io/6nqyf

    Walsh, M. (2024). It”s mostly an accompaniment to something. M/C Journal. https://doi.org/10.5204/mcj.3040

    Ycel, A. (2022). The expression of emotions through musical parameters during the covid-19 restrictions: a sentiment analysis on philippines spotify data. Uluslararas Ynetim Biliim Sistemleri ve Bilgisayar Bilimleri Dergisi. https://doi.org/10.33461/uybisbbd.1139568

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  • What Media Interventions Can Help Reduce Obesity and Overweight?

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    Research Suggestions at the end of the literature review

    Introduction

    Obesity and overweight are significant global health concerns (Wongtongtair, 2021), (Baranowski, 2015), (Selvaraj, 2024), with far-reaching consequences for individuals and healthcare systems. The pervasiveness of media in modern life presents both challenges and opportunities in addressing this epidemic. This review examines various media interventions designed to combat obesity and overweight, analyzing their effectiveness, limitations, and potential for future development. We will explore diverse approaches, including video games, mobile health applications, social media campaigns, mass media campaigns, and educational programs delivered through digital platforms. A critical evaluation of the existing literature will highlight successful strategies, identify research gaps, and propose avenues for improving future interventions.

    Video Games and Exergames as Interventions

    The potential of video games to influence health behaviors, particularly in relation to obesity, is a growing area of research (Baranowski, 2015). Tom Baranowski’s work (Baranowski, 2015) highlights “Games for Health” (G4H) as a promising approach, utilizing entertainment game technology to achieve health goals. A systematic review identified 28 studies, with 40% showing positive influences on obesity-related behaviors (Baranowski, 2015). Games targeting dietary changes have demonstrated success in increasing fruit and vegetable consumption (Baranowski, 2015), , , . However, the effectiveness of exergames, which incorporate physical activity into gameplay, may be limited without consistent supervision (Baranowski, 2015), , , . While exergames can provide intense workouts in controlled settings (Baranowski, 2015), , maintaining engagement and exertion levels outside of these environments poses a significant challenge (Baranowski, 2015). Further research is needed to understand how to sustain engagement and translate short-term gains into long-term lifestyle changes (Bissell, NaN), (Calcaterra, 2023). A study examining the effectiveness of Wii exergames on children’s enjoyment, engagement, and exertion in physical activity showed promising results (Bissell, NaN), suggesting that this type of media intervention could be a valuable tool. The games’ instructional models were effective in engaging children, potentially leading to increased energy expenditure and reduced sedentary behavior (Bissell, NaN). However, the study was a pilot study and further research is needed on larger populations, especially targeting those already battling obesity (Bissell, NaN).

    Mobile Health (mHealth) and Smartphone Applications

     The rise of smartphones and mobile technology has created new avenues for delivering health interventions (Wongtongtair, 2021), (Watanabe-Ito, 2020), (Seid, 2024), (Volkova, 2017). A study comparing mobile health education messages to face-to-face consultation for weight reduction in overweight female adolescents in Thailand found significant weight reduction in both intervention groups (Wongtongtair, 2021). This highlights the potential of mobile health education to empower individuals and improve health behaviors (Wongtongtair, 2021). Another study utilized a smartphone app for creating dietary diaries and social media interaction to promote healthy eating habits among college students (Watanabe-Ito, 2020). This intervention resulted in a significant increase in interest in eating habits and a decrease in self-evaluation of eating habits (Watanabe-Ito, 2020), suggesting that digital tools can effectively raise awareness and encourage critical thinking about dietary choices (Watanabe-Ito, 2020). A systematic review of randomized controlled trials confirmed that internet-based smartphone apps consistently improved consumers’ healthy eating behaviors (Seid, 2024). The review found that 52% of offline-capable smartphone apps were successful in promoting healthier eating habits, demonstrating the effectiveness of these interventions across diverse groups (Seid, 2024). However, a study evaluating a mobile health obesity prevention program in young children found no significant intervention effect on fat mass index when compared to a control group (Works, 2020), highlighting the need for well-designed and targeted interventions (Works, 2020). Recruitment strategies for smartphone-delivered interventions are also crucial, with social media advertising, particularly Facebook campaigns, proving effective (Volkova, 2017). Culturally relevant materials are essential for maximizing reach and engagement within diverse populations (Volkova, 2017).

    Social Media Campaigns and Interventions

    Social media platforms offer significant potential for reaching large audiences and promoting health behavior change (Luo, 2024), (Sendyana, 2024), (Selvaraj, 2024), (Rukmini, 2021), (Prybutok, 2024), (Acha, 2022), (Osei-Kwasi, NaN), (Modrzejewska, 2022), (Chen, 2024), (Bacheva, 2024). A narrative review synthesized evidence on the individual-level effects of social media campaigns related to healthy eating, physical activity, and healthy weight (Luo, 2024). The review found that actively engaging users tends to be more effective than passive information dissemination (Luo, 2024). A campaign designed to reduce sugar consumption among adolescents in Indonesia utilized Instagram and YouTube, delivering educational content about hidden sugars (Sendyana, 2024). While the campaign effectively increased knowledge (Rukmini, 2021), translating this knowledge into behavior change presented challenges (Rukmini, 2021). Another study in Indonesia focused on the impact of an Instagram campaign on healthy eating among college students (Rukmini, 2021). Although the campaign increased knowledge, it did not lead to significant changes in eating habits (Rukmini, 2021), suggesting that knowledge alone is insufficient for behavior change (Rukmini, 2021). A study examining the impact of obesity-related social media content on urban men in India found that attention to social media content positively influenced knowledge of health behaviors, leading to behavior change (Selvaraj, 2024). The study recommended frequent sharing of informative posts from health experts to raise awareness (Selvaraj, 2024). Social media can also create supportive communities, as demonstrated by a study showing that communication with friends on social media enhanced understanding of weight management conversations (Prybutok, 2024). However, challenges remain, including misinformation, privacy concerns, and the need for sustained engagement (Acha, 2022). A case study approach examined interventions using YouTube, Instagram, and Facebook, highlighting the importance of platform-specific features and community support (Acha, 2022). The study emphasized that social media interventions should augment, not replace, in-person treatment (Acha, 2022). A youth-led social marketing intervention in Spain utilized peer influence to promote healthy lifestyles, targeting socioeconomically disadvantaged youth (Llaurad, 2015). The intervention aimed to increase fruit and vegetable consumption and reduce screen time (Llaurad, 2015). Social media’s influence on body image and eating patterns is also significant (Modrzejewska, 2022), potentially contributing to obesity (Modrzejewska, 2022). However, social media can also be a valuable resource for obesity prevention and treatment, providing information and social support (Modrzejewska, 2022). A study in China linked digital media consumption to increased obesity rates among adolescents and young adults (Chen, 2024), highlighting the need for targeted interventions (Chen, 2024). A study in Bulgaria showed that social media is a primary source of information regarding healthy eating among youth (Bacheva, 2024), suggesting that targeted social media campaigns could be a powerful tool for promoting healthier lifestyles (Bacheva, 2024).

    Mass Media Campaigns

    Mass media campaigns have been employed to address obesity through public health messaging (Morley, 2018), (Falbe, 2017), (Kraak, 2021), (Gerberding, 2004), (Smith, 2015), (Dixon, 2018), (Capito, 2022). The LiveLighter campaign in Australia successfully reduced sugar-sweetened beverage consumption and increased water consumption among overweight and obese individuals (Morley, 2018). This multi-faceted campaign utilized television, radio, cinema, and online advertising (Morley, 2018). Another campaign focused on discouraging sugar-sweetened beverage consumption, highlighting their contribution to obesity, diabetes, and heart disease (Falbe, 2017). A systematic scoping review developed a typology of media campaigns to evaluate their collective impact on promoting healthy hydration behaviors and reducing sugary beverage health risks (Kraak, 2021). The typology included corporate advertising, social marketing, public information campaigns, and media advocacy (Kraak, 2021). The Centers for Disease Control and Prevention’s (CDC) VERB campaign utilized social marketing strategies to promote physical activity among tweens (Gerberding, 2004), showcasing the power of partnerships with athletes and celebrities (Gerberding, 2004). A study examining audience perceptions of mass media messages on physical activity revealed that messages about the risks of inactivity, particularly concerning obesity, were most readily recalled (Smith, 2015). However, there was a perceived lack of practical advice, indicating a need for more engaging and informative campaigns (Smith, 2015). The impact of unhealthy food sponsorship in sports on young adults’ food preferences was also investigated (Dixon, 2018), demonstrating that pro-health sponsorship models can enhance positive brand awareness (Dixon, 2018). Developing effective mass media campaigns requires careful consideration of messaging, target audience, and dissemination channels (Capito, 2022). Involving consumers in the campaign development process significantly enhances effectiveness (Capito, 2022).

    Educational Programs and Interventions

     Educational interventions, often delivered through media, play a crucial role in obesity prevention and treatment (Robinson, 2010), (Peterson, 2015), (Austin, 2012), (Mauriello, 2006), (Mandi, 2020), , (Gianfredi, 2021), (Binder, 2021). The Melbourne InFANT Program targeted first-time parents to influence child-focused obesity prevention (Hesketh, 2011), positively affecting maternal beliefs about television’s role in development and diet (Hesketh, 2011). This resulted in children in the intervention group watching less television and consuming more fruits and vegetables (Hesketh, 2011). The Healthy Choices program, a multi-component obesity prevention program targeting middle school students, showed significant increases in weight-related behaviors over three years, including increased fruit and vegetable consumption, reduced television watching, and increased physical activity (Peterson, 2015). The Planet Health intervention in Massachusetts middle schools demonstrated that higher exposure to lessons aimed at reducing television viewing was associated with lower odds of disordered weight control behaviors (Austin, 2012). A computer-based obesity prevention program for adolescents utilized individualized feedback based on readiness to engage in healthy behaviors (Mauriello, 2006), targeting television viewing reduction (Mauriello, 2006). A study promoting physical activity among medical students combined a web-based approach and motivational interviews (Mandi, 2020), demonstrating the effectiveness of multicomponent interventions (Mandi, 2020). A nutritional intervention using pictorial representations in Brazil significantly improved dietary knowledge and practices among adolescents , increasing vegetable consumption and reducing soft drink intake . The COcONUT project used theatrical and practical workshops to improve children’s adherence to the Mediterranean Diet (Gianfredi, 2021). A typology of persuasive strategies for presenting healthy foods to children was proposed, outlining composition-related, source-related, and information-related characteristics (Binder, 2021). The study highlighted the lack of conclusive studies on the effects of healthy food presentations compared to unhealthy ones (Binder, 2021), indicating a need for further research in this area (Binder, 2021).

    Addressing Specific Populations and Cultural Considerations

     The effectiveness of media interventions is influenced by cultural context and target audience (Osei-Kwasi, NaN), (Robinson, 2010), (Okpanachi, 2024), (Molenaar, 2021), (Aleid, 2024). A culturally tailored diet and lifestyle intervention for African and Caribbean people in Manchester utilized social media interactions and a fitness mobile application to enhance engagement and promote healthy behaviors (Osei-Kwasi, NaN). The study highlighted the benefits of a culturally tailored approach and an all-African delivery team (Osei-Kwasi, NaN). A community-based obesity prevention program for low-income African American girls included culturally tailored dance classes and a home-based intervention to reduce screen media use (Robinson, 2010). While BMI changes did not significantly differ between groups, secondary outcomes, such as improved cholesterol levels and reduced depressive symptoms, were observed (Robinson, 2010). The development of Food Villain, a serious game designed to influence healthy eating habits among African international students, addresses cultural, environmental, and behavioral factors impacting dietary choices (Okpanachi, 2024). The game’s web-based and virtual reality versions aim to enhance engagement and motivation (Okpanachi, 2024). A study examining young adults’ engagement with social media food advertising in Australia highlighted the influence of advertisements on food choices and perceptions of health (Molenaar, 2021). Participants expressed feelings of guilt related to unhealthy eating behaviors influenced by advertising (Molenaar, 2021). A study in Saudi Arabia found that social media food advertisements significantly influenced unhealthy eating behaviors, emphasizing the need for policy interventions to regulate food advertising and promote physical activity (Aleid, 2024).

    Framing Effects and Persuasive Strategies

    The way health messages are framed significantly impacts their effectiveness (Binder, 2020), (Faras, 2020), (Requero, 2021). A study investigating gain- and loss-framed nutritional messages found that gain-framed messages increased awareness and healthy eating behavior among children aged 6-10 (Binder, 2020). Children exposed to gain-framed messages showed a higher intake of fruits compared to the control group (Binder, 2020). Another study examined the effectiveness of fear versus hope appeals in health advertisements (Faras, 2020). Individual characteristics, such as self-efficacy and fast food consumption frequency, moderated the effectiveness of these appeals (Faras, 2020). The study highlighted the importance of tailoring messages to individual differences (Faras, 2020). A review explored how healthy eating campaigns can change attitudes and behaviors through persuasion processes (Requero, 2021). The review emphasized the significance of elaboration and perceived validity of thoughts in mediating persuasion (Requero, 2021). Different modalities of information presentation (verbal, visual, physical experiences) can also influence effectiveness (Requero, 2021).

    Parental Involvement and Family-Based Interventions

    Parental involvement plays a critical role in shaping children’s eating habits and physical activity levels (Lepeleere, 2017), (Hesketh, 2011), (Modrzejewska, 2022), (Haines, 2018), (, NaN), (, NaN). An online video intervention aimed at promoting positive parenting practices related to children’s physical activity, screen time, and diet showed some improvements in physical activity levels in older children (ages 10-12) (Lepeleere, 2017), but no significant effects on children’s diet were found (Lepeleere, 2017). The Melbourne InFANT Program showed promising impacts on parental attitudes and beliefs, influencing children’s diet and television viewing behaviors (Hesketh, 2011). Parental food preferences and knowledge significantly affect children’s food choices (Modrzejewska, 2022), and social media can further influence these behaviors (Modrzejewska, 2022). A home-based obesity prevention intervention among families with children aged 1.5 to 5 years showed significant improvements in fruit intake and a reduction in the percentage of fat mass in one intervention group compared to the control group (Haines, 2018). A review highlighted that long screen time negatively affects sleep duration and quality, which can contribute to obesity (, NaN). A weight management program based on self-determination theory (SDT) that included structured exercise and parental involvement showed improvements in psychological aspects, even though weight loss was not achieved (, NaN). The study highlighted the role of parental support and the importance of improving communication patterns within families (, NaN).

    Limitations and Future Directions

    While the studies reviewed demonstrate the potential of media interventions in addressing obesity and overweight, several limitations and research gaps need to be addressed. Many studies have limitations in terms of sample size, methodological rigor, and follow-up periods. Longitudinal studies are needed to assess the long-term effectiveness of interventions (Luo, 2024), (Acha, 2022). The effectiveness of interventions may vary across different populations and cultural contexts (Osei-Kwasi, NaN), (Robinson, 2010), (Okpanachi, 2024). More research is needed to understand the mechanisms through which media interventions influence behavior change (Anton, 2014). The role of individual characteristics, such as self-efficacy and motivation, needs further investigation (Faras, 2020), (Requero, 2021). The development of more engaging and culturally appropriate materials is crucial for maximizing reach and impact (Volkova, 2017), (Capito, 2022). Furthermore, the ethical considerations of using social media in health interventions, including data privacy and the potential for exacerbating health disparities, must be addressed (Acha, 2022). The integration of media interventions into broader community-based programs is also crucial for sustained impact (Jeffery, 2006). Finally, the cost-effectiveness of different media interventions needs to be evaluated to guide resource allocation (Volkova, 2017).

    Media interventions hold significant promise for reducing obesity and overweight. Various approaches, including video games, mobile health applications, social media campaigns, mass media campaigns, and educational programs, have demonstrated effectiveness in influencing dietary habits, physical activity levels, and other obesity-related behaviors. However, the effectiveness of these interventions varies greatly depending on factors such as the specific approach, target population, cultural context, and message framing. Future research should focus on addressing the limitations of existing studies, improving methodological rigor, and developing culturally tailored interventions that address the specific needs and challenges of different populations. A multi-pronged approach involving multiple sectors of society, including healthcare professionals, educators, policymakers, and the media, is essential for creating a supportive environment that encourages healthy eating and physical activity. By leveraging the power of media effectively, we can contribute significantly to combating the global obesity epidemic.

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    Capito, C., Martins, R., Feteira-Santos, R., Virgolino, A., Graa, P., Gregorio, M. J., & Santos, O. (2022). Developing healthy eating promotion mass media campaigns: a qualitative study. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2022.931116

    Chen, P. (2024). Obesity in adolescents and young adults in chinese digital media: individual causes, social implications, and policy perspectives. El Profesional de la Informacion. https://doi.org/10.3145/epi.2024.ene.0320

    Dixon, H., Scully, M., Wakefield, M., Kelly, B., Pettigrew, S., Chapman, K., & Niederdeppe, J. (2018). The impact of unhealthy food sponsorship vs. pro-health sponsorship models on young adults’ food preferences: a randomised controlled trial. BioMed Central. https://doi.org/10.1186/s12889-018-6298-4

    Falbe, J. & Madsen, K. A. (2017). Growing momentum for sugar-sweetened beverage campaigns and policies: costs and considerations. American Public Health Association. https://doi.org/10.2105/ajph.2017.303805

    Faras, P. (2020). The use of fear versus hope in health advertisements: the moderating role of individual characteristics on subsequent health decisions in chile. Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/ijerph17239148

    Gerberding, J. & Marks, J. (2004). Making america fit and trim–steps big and small. American Journal of Public Health. https://doi.org/10.2105/AJPH.94.9.1478

    Gianfredi, V., Bertarelli, G., Minelli, L., & Nucci, D. (2021). Promoting healthy eating in childhood: results from the coconut (children promoting nutrition throught theatre) project. Minerva Pediatrica. https://doi.org/10.23736/S2724-5276.21.06249-2

    Haines, J., Douglas, S., Mirotta, J. A., OKane, C., Breau, R., Walton, K., Krystia, O., Chamoun, E., Annis, A., Darlington, G., Buchholz, A., Duncan, A., Vallis, L., Spriet, L., Mutch, D., Brauer, P., Allen-Vercoe, E., Taveras, E., Ma, D., & Study, O. B. O. T. G. F. H. (2018). Guelph family health study: pilot study of a home-based obesity prevention intervention. Canadian journal of public health. https://doi.org/10.17269/s41997-018-0072-3

    Hesketh, K., Campbell, K., Crawford, D., Salmon, J., Ball, K., McNaughton, S., & McCallum, Z. (2011). O1-5.1cluster-randomised controlled trial of an early childhood obesity prevention program: the melbourne infant feeding, activity and nutrition trial (infant) program. Journal of Epidemiology and Community Health. https://doi.org/10.1136/jech.2011.142976a.36

    Jeffery, R. (2006). Community approaches to obesity treatment and prevention.

    Kraak, V. & Stanley, K. C. (2021). A systematic scoping review of media campaigns to develop a typology to evaluate their collective impact on promoting healthy hydration behaviors and reducing sugary beverage health risks. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph18031040

    Lepeleere, S. D., Bourdeaudhuij, I. D., Cardon, G., & Verloigne, M. (2017). The effect of an online video intervention movie models on specific parenting practices and parental self-efficacy related to childrens physical activity, screen-time and healthy diet: a quasi-experimental study. BioMed Central. https://doi.org/10.1186/s12889-017-4264-1

    Llaurad, E., AcevesMartins, M., Tarro, L., Papell-Garcia, I., Puiggrs, F., Arola, L., PradesTena, J., Montagut, M., Fernndez, C. M. M., Sol, R., & Giralt, M. (2015). A youth-led social marketing intervention to encourage healthy lifestyles, the eyto (european youth tackling obesity) project: a cluster randomised controlled0 trial in catalonia, spain. BioMed Central. https://doi.org/10.1186/s12889-015-1920-1

    Luo, Y., Maafs-Rodrguez, A. G., & Hatfield, D. P. (2024). The individuallevel effects of social media campaigns related to healthy eating, physical activity, and healthy weight: a narrative review. Obesity Science & Practice. https://doi.org/10.1002/osp4.731

    Mandi, D., Bjegovi-Mikanovi, V., Vukovic, D., Djikanovi, B., Stamenkovi,  .., & Lalic, N. (2020). Successful promotion of physical activity among students of medicine through motivational interview and web-based intervention. PeerJ. https://doi.org/10.7717/peerj.9495

    Mauriello, L., Driskell, M., Sherman, K., Johnson, S. S., Prochaska, J., & Prochaska, J. (2006). Acceptability of a school-based intervention for the prevention of adolescent obesity. Journal of School Nursing. https://doi.org/10.1177/10598405060220050501

    Modrzejewska, A., Czepczor-Bernat, K., Modrzejewska, J., Roszkowska, A., Zembura, M., & Matusik, P. (2022). #childhoodobesity a brief literature review of the role of social media in body image shaping and eating patterns among children and adolescents. Frontiers in Pediatrics. https://doi.org/10.3389/fped.2022.993460

    Molenaar, A., Saw, W. Y., Brennan, L., Reid, M., Lim, M. S. C., & McCaffrey, T. A. (2021). Effects of advertising: a qualitative analysis of young adults’ engagement with social media about food. Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/nu13061934

    Morley, B., Niven, P., Dixon, H., Swanson, M., McAleese, A., & Wakefield, M. (2018). Controlled cohort evaluation of the<i>livelighter</i>mass media campaigns impact on adults reported consumption of sugar-sweetened beverages. BMJ. Https://doi.org/10.1136/bmjopen-2017-019574

    Okpanachi, V. A. & Adaji, I. (2024). The design of food villain, a serious game to influence healthy eating habits among african international students. IEEE Games Entertainment Media Conference. https://doi.org/10.1109/GEM61861.2024.10585723

    Osei-Kwasi, H., Akparibo, R., Ojwang, A., Asamane, E., Olayanju, A., & Ellahi, B. (NaN). Design and implementation of a culturally tailored diet and lifestyle intervention for african and caribbean people residing in manchester: insights from a process evaluation. Proceedings of the Nutrition Society. https://doi.org/10.1017/s0029665122002592

    Peterson, K. E., Peterson, K. E., Spadano-Gasbarro, J. L., Greaney, M., Greaney, M., Austin, S. B., Austin, S. B., Mezgebu, S., Hunt, A., Blood, E., Horan, C. M., Feldman, H., Osganian, S., Bettencourt, M., & Richmond, T. K. (2015). Three-year improvements in weight status and weight-related behaviors in middle school students: the healthy choices study. PLoS ONE. https://doi.org/10.1371/journal.pone.0134470

    Prybutok, V. R., Prybutok, G., & Yogarajah, J. (2024). Social media influences on dietary awareness in children. None. https://doi.org/10.3390/healthcare12191966

    Requero, B., Santos, D., Cancela, A., Briol, P., & Petty, R. (2021). Promoting healthy eating practices through persuasion processes. Basic and Applied Social Psychology. https://doi.org/10.1080/01973533.2021.1929987

    Robinson, T., Matheson, D., Kraemer, H., Wilson, D. M., Obarzanek, E., Thompson, N. S., Alhassan, S., Spencer, T. R., Haydel, K., Fujimoto, M., Varady, A., & Killen, J. (2010). A randomized controlled trial of culturally tailored dance and reducing screen time to prevent weight gain in low-income african american girls: stanford gems.. Archives of Pediatrics & Adolescent Medicine. https://doi.org/10.1001/archpediatrics.2010.197

    Rukmini, E. & Adella, A. (2021). Healthy diet social media campaign among indonesian college students. None. https://doi.org/10.11591/IJPHS.V10I3.20842

    Seid, A., Fufa, D. D., & Bitew, Z. (2024). The use of internet-based smartphone apps consistently improved consumers” healthy eating behaviors: a systematic review of randomized controlled trials. None. https://doi.org/10.3389/fdgth.2024.1282570

     Selvaraj, S. N., Sriram, A., & S, S. (2024). Impact of obesity-related social media contents on urban men: application of the health belief model. ATHENS JOURNAL OF HEALTH & MEDICAL SCIENCES. https://doi.org/10.30958/ajhms.11-4-4

    Sendyana, I. N. T. & Rizkiantono, R. E. (2024). Perancangan kampanye pola hidup rendah gula melalui media sosial sebagai upaya pencegahan obesitas bagi remaja usia 16 -21 tahun. None. https://doi.org/10.12962/j29880114.v1i3.735

    Smith, B. J. & Bonfiglioli, C. (2015). Physical activity in the mass media: an audience perspective. Oxford University Press. https://doi.org/10.1093/her/cyv008

    Volkova, E., Michie, J., Corrigan, C., Sundborn, G., Eyles, H., Jiang, Y., & Mhurch, C. N. (2017). Effectiveness of recruitment to a smartphone-delivered nutrition intervention in new zealand: analysis of a randomised controlled trial. BMJ. https://doi.org/10.1136/bmjopen-2017-016198

    Watanabe-Ito, M., Kishi, E., & Shimizu, Y. (2020). Promoting healthy eating habits for college students through creating dietary diaries via a smartphone app and social media interaction: online survey study. JMIR mHealth and uHealth. https://doi.org/10.2196/17613

    Wongtongtair, S., Iamsupasit, S., Somrongthong, R., Kumar, R., & Yamarat, K. (2021). Comparison of mobile health education messages verses face-to-face consultation for weight reduction among overweight female adolescents in thailand. F1000Research. https://doi.org/10.12688/f1000research.51156.2

    Works, C. & Miller, J. (2020). Is prolotherapy effective in reducing pain and improving function in patients with knee oa?. None. https://doi.org/10.1097/ebp.0000000000000578

    Ideas For Quantitative Research  

    The global obesity epidemic presents a significant public health challenge (Gerberding, 2004), (Baranowski, 2015), (Tsai, 2019). Addressing this complex issue requires a multifaceted approach, with media interventions playing a crucial role in shaping health behaviors and promoting lifestyle changes (Luo, 2024), (Sendyana, 2024), (Kraak, 2021). However, existing research reveals significant knowledge gaps regarding the effectiveness, long-term impact, and optimal design of various media interventions (Mller, 2010), (Robinson, 2017), (Randolph, 2015). This document outlines ten quantitative research suggestions, directly addressing these knowledge gaps and proposing avenues for more effective obesity prevention and treatment strategies.

    Quantitative Research Suggestions

    Comparative Effectiveness of Mobile Health Interventions

    • Research Question: How do different mHealth interventions (e.g., text messaging, mobile apps with varying levels of interactivity, gamified apps) compare in their effectiveness in promoting weight loss and maintaining healthy behaviors in adults with obesity?

      Knowledge Gap: While some mHealth interventions have shown promise (Wongtongtair, 2021), (Randolph, 2015), a direct comparison of different approaches across a large and diverse population is lacking. The effectiveness of text messaging interventions, for instance, has yielded mixed results (Randolph, 2015).

      Methodology: A multi-arm RCT comparing multiple mHealth interventions. Participants would be randomly assigned to different intervention groups, each receiving a unique mHealth intervention. Outcome measures would include changes in BMI, waist circumference, physical activity levels, dietary habits, and self-reported adherence to the intervention.

    Effectiveness of Culturally Tailored Social Media Campaigns

    • Research Question: What is the effectiveness of culturally tailored social media campaigns in promoting healthy eating and physical activity among specific ethnic minority groups, compared to general population campaigns?

      Knowledge Gap: While social media interventions show promise (Luo, 2024), (Sendyana, 2024), (Rukmini, 2021), (Acha, 2022), the effectiveness of culturally tailored campaigns in specific populations remains understudied (Obita, 2023). Studies have shown varying results regarding the effectiveness of social media campaigns on behavior change.

      Methodology: A cluster-randomized controlled trial (CRCT) comparing culturally tailored campaigns to general population campaigns. Clusters could be schools or communities with significant populations of the target ethnic minority group. Outcome measures would include changes in BMI, dietary habits, physical activity levels, and knowledge of healthy lifestyle choices.

    Impact of Mass Media Campaigns on Sugar-Sweetened Beverage Consumption

    • Research Question: What is the impact of a comprehensive mass media campaign (television, radio, print, and online advertising) on the consumption of sugar-sweetened beverages (SSBs) and related health outcomes (BMI, waist circumference, blood glucose levels) among adults, compared to a control group?

      Knowledge Gap: While some mass media campaigns have shown success in reducing SSB consumption (Morley, 2018), further research is needed to evaluate the long-term effects and the optimal design of these campaigns (Falbe, 2017). The effectiveness of such campaigns can be significantly influenced by the presence of heavy commercial advertising promoting SSBs (Morley, 2018).

      Methodology: A controlled before-and-after study design. Data would be collected from a representative sample of adults before and after the campaign using surveys and physiological measurements. The control group would be a similar population in a geographical area not exposed to the campaign.

    The Role of Parental Education in Media Intervention Effectiveness

    • Research Question: How does maternal education level moderate the effectiveness of media interventions (e.g., online videos, mobile apps) aimed at improving children’s dietary habits and physical activity levels?

      Knowledge Gap: The effectiveness of interventions may vary based on parental characteristics (Ball, NaN). Higher educated mothers showed a more significant positive effect on their children’s vegetable consumption, while lower educated mothers saw a greater positive effect on their children’s water consumption due to the intervention (Ball, NaN).

      Methodology: An RCT comparing the effectiveness of a media intervention among children whose mothers have different levels of education. Outcome measures would include changes in children’s BMI, dietary habits, and physical activity levels. Moderation analysis would be conducted to assess the influence of maternal education on the intervention’s effectiveness.

    Influence of Food Advertising on Social Media on Eating Behaviors

    • Research Question: What is the relationship between exposure to unhealthy food advertising on social media and eating behaviors (fast food consumption, snacking frequency, fruit and vegetable intake) among young adults, considering the influence of algorithms and ad-blockers?

      Knowledge Gap: The pervasive influence of food advertising on social media on young adults’ eating behaviors is a significant concern (Molenaar, 2021). The use of ad-blockers and algorithms can further complicate this relationship.

      Methodology: A cross-sectional study using surveys and social media data analysis. Participants would complete questionnaires about their social media usage, exposure to food advertising, and eating behaviors. Social media data analysis would be used to assess actual exposure to food advertisements.

    Effectiveness of Peer-Led Social Media Interventions

    • Research Question: How effective are peer-led social media interventions in promoting healthy lifestyle choices (physical activity, healthy eating) among adolescents compared to interventions led by health professionals?

      Knowledge Gap: While peer influence is powerful (Llaurad, 2015), (Chung, 2021), a direct comparison of peer-led versus professional-led social media interventions is needed. Studies have shown that peer influence on social media can promote both healthy and unhealthy eating behaviors (Chung, 2021).

      Methodology: An RCT comparing peer-led and professional-led social media interventions. Adolescents would be randomly assigned to either a peer-led group or a professional-led group. Outcome measures would include changes in physical activity levels, dietary habits, and self-reported healthy lifestyle choices.

    Impact of Framing Effects on Health Messages

    • Research Question: How do different message framing strategies (gain-framed vs. loss-framed, fear appeals vs. hope appeals) influence the effectiveness of media interventions aimed at reducing unhealthy eating behaviors among children and adolescents?

      Knowledge Gap: The optimal framing of health messages for different age groups and behaviors remains unclear , , . Gain-framed messages have shown promise in increasing awareness and healthy eating behavior among young children .

      Methodology: An RCT comparing the effectiveness of different message framing strategies. Participants would be randomly assigned to different groups receiving messages with different frames. Outcome measures would include changes in knowledge, attitudes, and behaviors related to healthy eating.

    Effectiveness of Combining Media Interventions and Other Approaches

    • Research Question: What is the comparative effectiveness of integrating media interventions (e.g., mobile apps, social media campaigns) with other approaches (e.g., behavioral therapy, family-based interventions) in achieving weight loss and improving health outcomes in obese adults?

      Knowledge Gap: The synergistic effects of combining media interventions with other treatment modalities are not well understood (Dietz, 2006), (Hutfless, 2013), (Bray, NaN). Studies have shown that combining behavioral interventions with pharmacotherapy can lead to significant weight loss (Dietz, 2006).

      Methodology: An RCT comparing a combined intervention (media intervention plus another approach) to a control group receiving only the other approach. Outcome measures would include changes in BMI, waist circumference, physical activity levels, dietary habits, and quality of life.

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  • A Comprehensive Analysis of Changes in Video and Broadcast Distribution and Production

    admin

    Research Ideas at the end of the literature review

    SVOD, VOD, FAST, and Other Video Distribution Systems: A Comprehensive Analysis of Changes in Video and Broadcast Distribution and Production

    Introduction

    The landscape of video and broadcast distribution has undergone a dramatic transformation in recent years, driven by technological advancements and evolving consumer preferences. This shift has led to the emergence of new video distribution systems, including Subscription Video on Demand (SVOD), Video on Demand (VOD), and Free Ad-supported Streaming Television (FAST), alongside the continued evolution of traditional broadcasting methods. This analysis examines these systems, exploring their impact on both video distribution and production practices.

    Subscription Video on Demand (SVOD)

    SVOD services, epitomized by Netflix, represent a significant departure from traditional broadcasting models (Lobato, 2017). These platforms offer a vast library of content, accessible on demand for a recurring subscription fee (Vacas-Aguilar, 2021). The success of SVOD hinges on several key factors. First, the availability of high-speed internet access has enabled the widespread adoption of streaming technology (Loebbecke, NaN). Second, the ability to binge-watch entire series at one’s own pace has fundamentally altered viewing habits (Boca, 2019), (Zndel, NaN). Third, SVOD providers have invested heavily in original content, creating exclusive programming that attracts and retains subscribers (Iordache, 2021), (Iordache, 2022). This investment in original content has had a profound impact on the television industry, changing production strategies and forcing traditional broadcasters to adapt (Llamas-Rodriguez, 2020). The international expansion of SVOD platforms like Netflix has also impacted national distribution ecosystems, creating both opportunities and challenges for local producers (Papadimitriou, 2020). Furthermore, SVOD services are increasingly leveraging AI and machine learning to enhance content quality, personalize recommendations, and optimize streaming efficiency (Mrak, 2019), (Khandelwal, 2023). However, the dominance of US platforms in many international markets raises concerns about content diversity and the potential marginalization of local productions (Iordache, 2021). The financial strategies employed by major SVOD players, including their approach to content acquisition and spending, have also undergone significant shifts, particularly in response to the COVID-19 pandemic (Das, 2024).

    Video on Demand (VOD)

    VOD services offer a broader range of content access models compared to SVOD. While some VOD platforms operate on a transactional basis, charging per view, others offer subscription-based access to a curated library of content (Loebbecke, NaN). The rise of VOD, along with SVOD, has significantly altered the television series industry, impacting production, distribution, and consumption patterns (Boca, 2019). The evolution of VOD is closely tied to technological advancements in broadband connectivity and storage capacities (Loebbecke, NaN). Early attempts to introduce interactive and on-demand services, though not always commercially successful, paved the way for the widespread adoption of VOD platforms (Loebbecke, NaN). The COVID-19 pandemic accelerated the shift towards subscription payment models in the VOD market, further highlighting the evolving dynamics of this sector (Mitrov, 2020). VOD services, like SVOD, also face challenges related to content diversity and the potential dominance of larger, international platforms (Kotlinska, 2024). The impact of VOD on the audiovisual industry’s business model is significant, requiring content creators and distributors to adapt to new media consumption trends and optimize recommendation algorithms (Kotlinska, 2024).

    Free Ad-supported Streaming Television (FAST)

    FAST channels provide free access to streaming television content, supported by advertising revenue (Herbert, 2018). This model represents a hybrid approach, combining elements of traditional broadcasting (linear programming) with the on-demand accessibility of streaming services (Herbert, 2018). The emergence of FAST channels has broadened access to streaming content, particularly for viewers who may be unwilling or unable to pay for subscription services (Herbert, 2018). FAST channels often provide curated content, focusing on specific genres or demographics (Herbert, 2018). The advertising model, however, presents challenges in terms of revenue generation and the potential for intrusive advertising experiences. The impact of FAST services on traditional broadcast models is still developing, but their increasing popularity suggests a significant shift in how viewers consume free television content (Herbert, 2018). The business models of FAST channels are still evolving, and further research is needed to understand their long-term sustainability and impact on the broader video distribution landscape (Herbert, 2018).

    Other Video Distribution Systems

    Beyond SVOD, VOD, and FAST, several other video distribution systems are emerging and evolving. These include:

    Live Streaming Services (SLSSs): These platforms enable real-time broadcasting of video content, often with interactive elements (Fietkiewicz, NaN). SLSSs have transformed information production and consumption patterns, allowing for more interactive and synchronous viewer engagement (Fietkiewicz, NaN). The motivational factors for both streamers and viewers are diverse and influence production and distribution strategies (Fietkiewicz, NaN). The commercial use of live streaming is also growing, adding another layer to the evolving video distribution landscape (Fietkiewicz, NaN).

    Mobile Video on Demand (VoD): The proliferation of smartphones and improved mobile network technologies has fueled the growth of mobile VoD services (Dyaberi, 2010). Challenges remain in terms of offloading video data from congested networks and optimizing delivery for different network conditions (Dyaberi, 2010). Dynamic pricing strategies may also play a role in enhancing the consumer experience and optimizing network resource use (Dyaberi, 2010).

    Traditional Broadcasting: While facing significant competition from streaming services, traditional broadcasting continues to evolve. The transition from analogue to digital terrestrial television has transformed broadcasting in many regions (Given, 2016). Broadcasters are adapting by offering online content and incorporating new technologies like AI to enhance production efficiency (Mrak, 2019). However, challenges remain in terms of audience measurement and adapting to changing viewing habits (Given, 2016).

    Changes in Video Production

    The shift towards streaming has profoundly impacted video production practices. The rise of SVOD has led to increased investment in original content, particularly in genres like scripted series and documentaries (Iordache, 2021), (Iordache, 2022). This has spurred innovation in production techniques, storytelling, and creative approaches (Iordache, 2021). The demand for high-quality video content, especially in formats like 360 VR video, presents technical challenges related to production and distribution (Khan, NaN). AI and machine learning are also transforming production efficiency, enabling cost-effective restoration of historical content and automating traditional tasks (Mrak, 2019). The increasing involvement of AI in production, however, raises concerns about bias and ethical considerations (Khandelwal, 2023). The COVID-19 pandemic significantly disrupted production schedules and workflows, forcing adaptations in remote production techniques and impacting content output (Mitrov, 2020), (Das, 2024). In addition, the shift toward streaming has also impacted the role of paratexts in television, with elements like episodic recaps being reworked or omitted to facilitate binge-watching (Zndel, NaN). The production of content for specific platforms, such as the creation of original French-language series for Canadian SVOD services (Boisvert, 2024), highlights the need to consider local audience demands and cultural contexts.

    Changes in Broadcast Distribution

    The transition from traditional broadcasting to streaming has fundamentally altered distribution methods. The rise of SVOD, VOD, and FAST channels has created a highly competitive market, forcing traditional broadcasters to adapt their strategies (Vacas-Aguilar, 2021), (Loebbecke, NaN). The shift from linear programming to on-demand access has significantly impacted viewing habits and audience engagement (Boca, 2019), (Zndel, NaN). The distribution of content across multiple platforms, including social media, has added complexity to distribution strategies (Mackay, 2017). The increasing reliance on digital distribution channels has also raised concerns about content security and piracy (Stolikj, NaN). The global reach of streaming platforms has blurred geographical boundaries, impacting the flow of international television programs and creating both opportunities and challenges for local producers and broadcasters (Lobato, 2017), (Papadimitriou, 2020), (Evans, 2016). The regulatory landscape surrounding digital platforms and content distribution is also evolving, raising questions about the role of government intervention in managing the digital media market (Winseck, 2021). Furthermore, the technical challenges related to delivering high-quality video content over diverse network conditions continue to drive innovation in distribution technologies (Dimopoulos, 2016), (Zhang, 2018).

    Challenges and Future Directions

    The transition to new video distribution systems presents numerous challenges. These include:

    • Content Diversity and Local Production: The dominance of large international platforms raises concerns about the potential marginalization of local productions and the homogenization of content (Iordache, 2021), (Milosavljevic, 2024).
    • Content Security and Piracy: The ease of accessing and sharing digital content online has led to increased piracy, posing significant challenges for content creators and distributors (Stolikj, NaN).
    • Regulation and Governance: The rapid evolution of digital platforms necessitates ongoing discussions about the appropriate regulatory frameworks for managing content distribution and protecting consumer interests (Winseck, 2021).
    • Technological Advancements: Keeping pace with technological advancements in areas like AI, VR, and mobile technologies requires continuous innovation in production and distribution techniques (Mrak, 2019), (Khan, NaN), (Dyaberi, 2010).
    • Financial Sustainability: The business models of various video distribution systems are still evolving, and the long-term financial sustainability of some models, particularly FAST channels, remains uncertain (Das, 2024), (Herbert, 2018).
    • Library Access: Libraries face challenges in providing access to consumer-licensed multimedia content due to digital rights management and the limitations of proprietary streaming services (Cross, NaN).

      The future of video and broadcast distribution will likely involve a continued convergence of traditional and new technologies, with a greater emphasis on personalized experiences, interactive content, and innovative business models. Further research is needed to fully understand the long-term impact of these changes on the media landscape, including their effects on content production, distribution strategies, audience engagement, and the broader cultural implications of media consumption (Herbert, 2018), (Boisvert, 2024). The ongoing interplay between technological advancements, evolving consumer preferences, and regulatory frameworks will shape the future of video distribution for years to come. The role of AI and machine learning in enhancing video quality, personalizing recommendations, and optimizing streaming efficiency will only increase in importance (Mrak, 2019), (Khandelwal, 2023). The development of new technologies, such as those related to 360 VR video streaming, will also continue to transform the production and consumption of video content (Khan, NaN). Moreover, the continued growth of mobile video consumption and the challenges associated with offloading video data from congested networks will necessitate further innovation in mobile video distribution strategies (Dyaberi, 2010). Finally, the evolving relationship between traditional broadcasters, streaming platforms, and libraries will significantly shape how video content is accessed and consumed in the future (Cross, NaN), (Given, 2016). The integration of sustainable practices into audiovisual production will also become increasingly important (Kotlinska, 2024), reflecting a growing awareness of environmental and social responsibilities within the media industry. The evolution of video and broadcast distribution is a complex and dynamic process. The emergence of SVOD, VOD, FAST, and other video distribution systems has fundamentally reshaped how video content is produced, distributed, and consumed. While these changes have brought numerous benefits, including increased access to content and personalized viewing experiences, they also present significant challenges related to content diversity, security, regulation, and financial sustainability. Understanding these challenges and adapting to the ongoing changes in the media landscape will be crucial for ensuring the continued success and evolution of the video industry. The integration of technological advancements, evolving consumer preferences, and adaptable business models will define the future of video distribution.

    Research Gaps and Suggestions for Research

    Research Gap 1: Longitudinal Impact of SVOD on National Audiovisual Ecosystems

    While several papers examine the immediate impact of SVOD platforms (like Netflix) on national audiovisual markets (Lobato, 2017), (Papadimitriou, 2020), (Iordache, 2021), (Iordache, 2021), a longitudinal study is needed. This research should track the long-term effects of SVOD on local production, distribution channels, and audience consumption habits across various countries. It would be beneficial to compare countries with differing levels of media market maturity and regulatory environments to analyze the diverse impacts of SVOD’s global presence. The study should utilize mixed methods, combining quantitative data on market shares and production volumes with qualitative data from interviews with industry stakeholders and audience surveys.

    Research Gap 2: Comparative Analysis of FAST Channel Business Models and Sustainability

    The emergence of FAST channels presents a new hybrid model in video distribution (Fietkiewicz, NaN). However, the long-term financial sustainability of these ad-supported platforms remains uncertain (Vacas-Aguilar, 2021). A comparative analysis of diverse FAST channel business models is needed, examining their revenue streams, cost structures, and audience engagement strategies. The research should assess the effectiveness of different advertising strategies and explore the potential for diversification into subscription models or other revenue streams. Furthermore, the study should analyze the impact of FAST channels on traditional broadcasting and SVOD services, considering the potential for competition and collaboration.

    Research Gap 3: The Role of Paratexts in Streaming Platforms and Viewer Engagement

    The impact of streaming platforms on traditional television viewing habits is well-documented (Zndel, NaN), (Lobato, 2017), but further research is needed to understand the role of paratexts (e.g., episodic recaps, opening credits) in shaping viewer experience. A comparative analysis of how different streaming services utilize (or omit) paratexts, and their effect on binge-watching behaviors and audience engagement, is crucial. The study should explore whether the absence of traditional paratexts leads to altered narrative comprehension and emotional responses among viewers. Qualitative methods, including user interviews and focus groups, could provide valuable insights into viewer perceptions and experiences.

    Research Gap 4: The Impact of AI on Content Diversity and Representation in Streaming Services

    While the use of AI in SVOD platforms for personalized recommendations and content optimization is discussed (Khandelwal, 2023), (Kotlinska, 2024), a critical examination of AI’s impact on content diversity and representation is lacking. Research is needed to investigate whether algorithmic biases in recommendation systems lead to the underrepresentation of certain genres, creators, or cultural perspectives. This research should analyze the algorithms used by various streaming services and assess their impact on content visibility and audience exposure to diverse voices. The study should also consider the ethical implications of AI-driven content curation and explore methods for mitigating algorithmic bias.

    Research Gap 5: Cross-Cultural Study of Audience Preferences and Consumption Patterns in SVOD

    Existing research often focuses on specific national contexts or regions (Papadimitriou, 2020), (Given, 2016), (Milosavljevic, 2024) but lacks a comprehensive cross-cultural comparison of audience preferences and consumption patterns in SVOD. A study comparing audiences across different cultural contexts, considering factors such as language, cultural values, and media consumption habits, is needed. This research should investigate how cultural factors influence the appeal of different genres, original programming, and overall platform usage. Qualitative methods, such as audience surveys and interviews, would be particularly valuable in understanding the nuanced cultural influences on SVOD consumption.

    Research Gap 6: The Impact of Mobile Video on Demand on Network Infrastructure

    The growth of mobile VoD is closely linked to advancements in smartphone technology and wireless networks (Dyaberi, 2010). However, a deeper understanding of its impact on network infrastructure is required. A study focusing on network congestion, resource allocation, and the effectiveness of different offloading strategies (e.g., using Wi-Fi) is needed. The research should analyze the relationship between network performance, video quality, and user experience in mobile VoD. Quantitative data on network traffic, bandwidth utilization, and user engagement metrics would be essential for this analysis.

    Research Gap 7: Comparative Study of Investment Strategies in Original Content Across Streaming Services

    While some papers analyze investment strategies of specific platforms (Vacas-Aguilar, 2021), (Iordache, 2021), (Iordache, 2022), (Iordache, 2021), a comprehensive comparative study analyzing original content investment strategies across different SVOD and VOD platforms is needed. This research should compare investment patterns in terms of genre, budget, production location, and target audiences. The study should analyze the factors driving investment decisions and assess their impact on platform success and content diversity. Quantitative data on investment amounts, production costs, and audience engagement metrics would be crucial.

    Research Gap 8: The Influence of Streaming Services on Local Cultural Identity

    The global reach of streaming platforms has blurred geographical boundaries and impacted the flow of international television programs (Papadimitriou, 2020), (Given, 2016), (Llamas-Rodriguez, 2020). However, a deeper exploration of the influence of streaming services on local cultural identity is needed. A comparative study focusing on the impact of streaming on local content production, cultural representation, and audience perceptions is needed. The research should investigate how streaming platforms balance global reach with local cultural relevance and consider the potential for cultural homogenization or the preservation of local cultural identities. Qualitative methods, such as interviews with filmmakers and audiences, would be crucial in understanding the subtle impacts on cultural identity.

    Research Gap 9: The Legal and Ethical Implications of AI in Video Production and Distribution

    The increasing use of AI in video production and distribution , (Khandelwal, 2023) raises significant legal and ethical questions. Research is needed to explore issues such as algorithmic bias, copyright infringement, and data privacy. The study should examine the existing legal frameworks and regulatory mechanisms related to AI in the media industry and assess their adequacy in addressing the emerging challenges. It should also consider the ethical implications of AI-driven decision-making in content creation and distribution and propose guidelines for responsible AI development and implementation.

    Research Gap 10: The Future of Libraries in the Streaming Era

    Libraries face significant challenges in providing access to consumer-licensed multimedia content (Cross, NaN). A study exploring the evolving role of libraries in the streaming era is needed. This research should investigate innovative approaches to providing access to digital media, considering factors such as licensing agreements, digital rights management, and the integration of streaming services into library collections. The study should explore potential partnerships between libraries and streaming platforms and propose strategies for ensuring equitable access to digital content for all library patrons. The study should also consider the implications for library services, staffing, and resource allocation.

    This outline of research gaps and suggestions aims to stimulate further inquiry into the evolving landscape of video distribution. Addressing these gaps will significantly enhance our understanding of the complex interplay between technology, culture, and the business of video.

    References

    1. Lobato, R. (2017). Rethinking international tv flows research in the age of netflix. SAGE Publishing. https://doi.org/10.1177/1527476417708245
    2. Vacas-Aguilar, F. (2021). El mercado del vdeo en streaming: un anlisis de la estrategia de disney+. El Profesional de la Informacion. https://doi.org/10.3145/EPI.2021.JUL.13
    3. Loebbecke, C. (NaN). Video content services as a transforming industry.
    4. Boca, P. (2019). Good things some to those who binge: an exploration of binge-watching related behavior. Babe-Bolyai University. https://doi.org/10.24193/jmr.34.1
    5. Zndel, J. (NaN). Serial skipper: netflix, binge-watching and the role of paratexts in old and new televisions.
    6. Iordache, C., Raats, T., & Afilipoaie, A. (2021). Transnationalisation revisited through the netflix original: an analysis of investment strategies in europe. SAGE Publishing. https://doi.org/10.1177/13548565211047344
    7. Iordache, C., Raats, T., & Mombaerts, S. (2022). The netflix original documentary, explained: global investment patterns in documentary films and series. Taylor & Francis. https://doi.org/10.1080/17503280.2022.2109099
    8. Llamas-Rodriguez, J. (2020). Luis miguel: la serie, class-based collective memory, and streaming television in mexico. None. https://doi.org/10.1353/cj.2020.0035
    9. Papadimitriou, L. (2020). Digital film and television distribution in greece: between crisis and opportunity. Springer International Publishing. https://doi.org/10.1007/978-3-030-44850-9_10
    10. Mrak, M. (2019). Ai gets creative. None. https://doi.org/10.1145/3347449.3357490
    11. Khandelwal, K. (2023). A study to know – use of ai for personalized recommendation, streaming optimization, and original content production at netflix. International journal of scientific research and engineering trends. https://doi.org/10.61137/ijsret.vol.9.issue6.119
    12. Iordache, C. (2021). Netflix in europe: four markets, four platforms? a comparative analysis of audio-visual offerings and investment strategies in four eu states. SAGE Publishing. https://doi.org/10.1177/15274764211014580
    13. Das, J. H. (2024). Lights, camera, capital: analyzing financial tactics in the streaming entertainment landscape. International Journal of Science and Research Archive. https://doi.org/10.30574/ijsra.2024.11.1.0190
    14. Mitrov, H. (2020). Television market development during the covid-19 pandemic. None. https://doi.org/10.32839/2304-5809/2020-10-86-9
    15. Kotlinska, M. (2024). The influence of digital transformation on the evolution of the audiovisual industry. EUROPEAN RESEARCH STUDIES JOURNAL. https://doi.org/10.35808/ersj/3702
    16. Herbert, D., Lotz, A. D., & Marshall, L. (2018). Approaching media industries comparatively: a case study of streaming. SAGE Publishing. https://doi.org/10.1177/1367877918813245
    17. Fietkiewicz, K. & Zimmer, F. (NaN). Introduction to the live streaming services minitrack. None. https://doi.org/None
    18. Dyaberi, J. M., Kannan, K. N., Pai, V. S., Chen, Y., Jana, R., Stern, D., & Wei, B. (2010). Scholastic streaming: rethinking mobile video-on-demand in a campus environment. None. https://doi.org/10.1145/1878022.1878035
    19. Given, J. (2016). There will still be television but i dont know what it will be called!: narrating the end of television in australia and new zealand. Cogitatio. https://doi.org/10.17645/mac.v4i3.561
    20. Khan, K. (NaN). Advancements and challenges in 360 virtual reality video streaming: a comprehensive review of cloud-based solutions. International journal of advanced networking and applications. https://doi.org/10.35444/ijana.2024.15408
    21. Boisvert, S. (2024). Streaming diversit: exploring representations within french-language scripted series on canadian svod services. None. https://doi.org/10.1177/13548565241270691
    22. Mackay, H. (2017). Social media analytics: implications for journalism and democracy 1. None. https://doi.org/None
    23. Stolikj, M., Jarnikov, D., & Wajs, A. (NaN). Artificial intelligence in media making security smarter. None. https://doi.org/None
    24. Evans, E., McDonald, P., Bae, J., Ray, S., & Santos, E. (2016). Universal ideals in local realities. SAGE Publishing. https://doi.org/10.1177/1354856516641629
    25. Winseck, D. (2021). Growth and upheaval in the network media economy in canada, 1984-2020. None. https://doi.org/10.22215/gmicp/2021.1
    26. Dimopoulos, G., Leontiadis, I., Barlet-Ros, P., & Papagiannaki, K. (2016). Measuring video qoe from encrypted traffic. ACM/SIGCOMM Internet Measurement Conference. https://doi.org/10.1145/2987443.2987459
    27. Zhang, B., Jin, X., Ratnasamy, S., Wawrzynek, J., & Lee, E. A. (2018). Awstream. None. https://doi.org/10.1145/3230543.3230554
    28. Milosavljevic, I. (2024). Domestic video streaming services – characteristics, offer and perception of users in serbia. MEDIA STUDIES AND APPLIED ETHICS. https://doi.org/10.46630/msae.2.2024.03
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  • The Relentless, Inevitable March of the Creator Economy

    Ideas for Research Topics at the bottom.

    DOUG SHAPIRO, DEC 1

    How Big it Is and Why it Will Keep Growing at the Expense of Corporate Media

    Imagine that from the time you were young, you worked hard to join a very exclusive, powerful club. Eventually, you made it, cementing your steadfast, lifelong belief that you, among very few, belonged there.

    Then, another club opened next door. It let everyone in. It felt like a mockery of what you had achieved. But it kept growing, attracting more members, siphoning off more attention. Young people fantasized about joining that club, not yours. Your club now seemed stodgy and out of step. It would challenge some of your fundamental beliefs about yourself.

    This describes how many in traditional media feel about so-called “creators.” They regard them as “less than,” crassly commercial, and certainly not artists. A recent dust up about The Hollywood Reporterchristening a new Creator A-List is illustrative. As Justine Bateman tweeted at the time, this is a list “…of infomercial salespeople. It’s not Hollywood.” 

    Whatever one’s value judgments—whether the creator economy is a positive, democratizing force, or a bastardization of art and full of self-promotional hucksters, or something in between—numbers don’t lie. It is growing rapidly at the expense of traditional media and, as I explain below, will inevitably continue to do so. 

    Tl;dr:

    • Let’s subdivide the media and entertainment (M&E) market into the corporate media economy and the creator media economy. Since M&E overall isn’t growing much, the relationship between the two is mostly zero-sum.
    • Based on a bottoms-up analysis of the largest creator media outlets, I estimate that the creator media economy generated close to $250 billion in revenue last year, roughly 10% of the global M&E market. It is growing far faster and over the last four years accounted for almost half of global M&E growth. Conservatively, I estimate it will exceed $600 billion and 20% of global M&E revenue by 2030. 
    • There are very powerful technological, cultural, demographic and economic reasons it could grow even faster than this: 
    • 1) Even absent GenAI, the volume of creator content should grow much faster than corporate media as creation gets ever more accessible; 
    • 2) GenAI will trigger a tsunami of creator content across media. Just as bits became the atomic unit to distribute information goods, tokens are becoming an atomic unit for the creation of information goods; 
    • 3) The quality distinction between corporate media content and the best creator content will continue to narrow; 
    • 4) Falling trust in institutions and rising demand for authenticity structurally favor creators; 
    • 5) Monoculture is in decline as consumers atomize into microcultures, disadvantaging the traditional media business model; 
    • 6) Demographics are destiny, and younger demos spend much more time with creator content; and
    • 7) The current monetization gap for the creator media economy (the delta between time share and dollar share) should narrow over time.
    • All this is mixed news for creators and creatives. For traditional media, there are only two choices: figure out how to participate in the creator economy or accept a perpetually diminishing business. 

    Defining the Creator (Media) Economy

    Let’s establish some definitions. 

    There isn’t a consensus definition of “creator.” Sometimes creators are considered synonymous with influencers. That’s relatively narrow, because it confines the creator economy mostly to Instagram, TikTok and YouTube. Sometimes creators are considered those who distribute content online strictly to commercialize it. On a recent episode of The Colin and Samir Show, Samir drew the distinction between a creator and a creative:

    …a creator is someone with a distribution mind. They’re thinking about what do I make that’s going to reach the most amount of people? They’re an independent media company….And they’re trying to solve how they can get their content seen at a large scale on platforms…A creative is working on the craft, right? They’re working on the skill set and they typically get hired to direct stuff or support other people in making their thing.

    Figure 1. The Corporate Media Economy

    Source: Author.

    Figure 2. The Corporate Media Economy (Redux)

    Source: Author.

    Since I focus on the business of media, to me the most interesting distinction is between traditional media, or what we could call corporate media, and creator media. Let’s define two, mutually-exclusive, economies: 

    • The corporate media economy is the ecosystem of traditional content creation, distribution and monetization, which usually entails institutional ownership, centralized decision making, portfolio-level risk management and several intermediaries between creative¹ and consumer who provide financing, marketing and distribution (Figure 1). As shown in Figure 2, most of the household names in the media and entertainment business are intermediaries.
    • The creator media economy, as I’m defining it here, encompasses all other media monetization. It is the ecosystem of content creation activities in which independent creators create content on a self-directed basis, they have a direct relationship with consumers, and this content is monetized. The passive voice in the last clause signifies that the content is monetized by someone, even if not by the creators themselves. (So, under this definition, everyone who posts anything that generates revenue is a creator, even if it is Meta or X/Twitter who monetizes it, not them.) (Figure 3.) A gray areas is small independent teams, of, say, 50 people or fewer. I put these in the creator category. Mr. Beast runs a full-fledged production company, with multi-million dollar budgets, but for these purposes he is a creator.²

    Figure 3. The Creator Media Economy

    Source: Author.

    The Relationship Between Corporate Media and Creator Media is Zero Sum

    As I have written about before (like here and here), the overall media and entertainment (M&E) market is not growing much globally, slightly less than the rate of inflation (Figure 4).

    Figure 4. Globally, Media Isn’t Growing on a Real Basis

    Source: PwC and Omdia, via Statista, IMF, Author analysis.

    The reason is that time spent with media has stagnated in recent years. It grew with the advent of mobile starting in 2008 and then had a COVID bump in 2020, but has been flat or declined since (Figure 5). Since M&E revenue is derived by monetizing consumer time and engagement, it is tough for the overall market to grow faster than inflation if time spent is not growing.

    Since M&E revenue is derived by monetizing consumer time and engagement, it is tough for the overall market to grow if time spent is not.

    Figure 5. Time Spent is Not Growing Either

    Source: eMarketer, April 2022.

    As mentioned, my intention is that these two economies are mutually exclusive and cumulatively exhaustive (or MECE, as they say in consulting land). Every dollar of end-market M&E revenue is either one or the other. As there is only one pool of consumer time, the relationship between the corporate and creator media economies is largely zero sum. The growth in the latter mostly comes at the expense of the former.  

    Creators Generate Revenue on a Lot of Platforms

    Under my definition above, creators’ work is monetized (there’s the passive voice again) on a wide variety of outlets and platforms. These include:

    • Social Networking (Meta, YouTube, Douyin, TikTok, Kuashiou, Snap, Pinterest, X, Bilibili, Weibo, VK, etc.)
    • Patronage/Community (OnlyFans, Patreon, Discord, etc.)
    • Gaming (Mobile Gaming, Steam, Epic, Roblox)
    • Livestreaming (Twitch, Bigo Live, Huya, DouYu)
    • Music (Spotify, Apple Music, Soundcloud, Bandcamp, etc.)
    • Podcasting
    • Influencer Marketing
    • Writing (Substack, Medium, Ghost, Beehiiv, etc.)

    The proportion of total revenue on these outlets that is attributable to creators can range from very little to all of it. 

    For instance, in gaming, a relatively small proportion of mobile game (iOS and Google Play) revenue is attributable to independent developers (I estimate ~5-10%), slightly more for Epic, slightly more for Steam, and, for Roblox, almost all revenue is attributable to independent developers (other than the few games that Roblox creates itself). In music, Spotify reported that the major labels and Merlin accounted for 74% of streams last year, so we can attribute ~25% of revenue to independent and individual creators, but almost all of the revenue on Bandcamp likely comes from creators. On social networking and patronage platforms like Patreon, the majority or virtually all of the revenue is attributable to creators. Likewise, influencer marketing represents the sponsorship fees paid by brands directly to influencers and so is also 100% attributable to creators. This continuum of creator attribution can be seen in Figure 6.

    Figure 6. The Proportion of Revenue Attributable to Creators Varies Widely

    Source: Company reports, Author estimates.

    How Big is It?

    In Figure 7, I show my bottoms-up estimate of the aggregate end-market revenue of the creator media economy, i.e., all advertising, subscription and transactional revenue attributable to creator content, globally. I derived this by applying the proportions in Figure 6 to the reported or estimated revenue for each outlet. As shown, I calculate that total creator media economy revenue was a little shy of $250 billion last year.

    Figure 7. The Creator Media Economy Approached $250 Billion Globally Last Year

    Source: Company reports, eMarketer, Statista, Sacra, Wall Street Zen, Fast Company, Video Game Insights, MoffettNathanson, The Information, Influencer Marketing Hub, CB Insights, Music Business Worldwide, Author estimates.

    Figure 8 compares creator media economy revenue to the total global M&E market, the nominal estimates shown above in Figure 4 (as estimated by PwC and Omdia). Last year, the creator media economy was almost 10% of the total $2.5 trillion M&E market. It has also, obviously, been growing much faster. While PwC estimates that the total M&E has grown at 5% annually over the past four years, I estimate that the creator media economy has grown 25% per year. So, although it is a relatively small portion of the total M&E market, it has accounted for almost half the growth.

    The creator media economy has accounted for about half of total M&E revenue growth over the last four years.

    Figure 8. The Creator Media Economy is ~10% of Global M&E and Half its Growth

    Source: Company reports, PwC and Omdia, eMarketer, Statista, Sacra, Wall Street Zen, Fast Company, Video Game Insights, MoffettNathanson, Influencer Marketing Hub, CB Insights, Music Business Worldwide, Author estimates.

    The Creator/Independent Media Economy Will Inevitably Keep Taking Share

    A simple math exercise shows how much larger and relatively more important the creator media economy will be by the end of the decade, if it keeps growing anywhere close to its recent pace.³ Presuming that the total M&E market grows in line with the PwC and Omdia estimate of ~3% through the end of the decade, then:

    • If the creator media economy grows at 10% annually, by 2030 it will be $460 billion and 15% of the M&E market; 
    • If it grows at 15% growth annually it would reach $630 billion and exceed 20% of the market; 
    • And, at 20% annual growth it would approach $850 billion and 30% of the market.

    Figure 9 shows the mid case, 15% annual growth.

    Figure 9. The Creator Media Economy Could Easily Reach ~20% of Global M&E by the End of the Decade

    Source: Company reports, PwC and Omdia, eMarketer, Statista, Sacra, Wall Street Zen, Fast Company, Video Game Insights, MoffettNathanson, Influencer Marketing Hub, CB Insights, Music Business Worldwide, Author estimates.

    Since no one likes wishy washy, let’s go with a point estimate: I forecast that the creator media economy will more than double by the end of the decade, exceeding $600 billion and 20% of the entire M&E market. 

    Powerful technological, cultural and demographic trends are tailwinds for the creator economy.

    But there are a whole host of reasons—powerful technological, cultural, demographic and economic trends—why it could grow even faster than that. Let’s walk through them.

    1. The Volume of Creator Content Will Keep Growing Fast (Even Without GenAI)

    There is already a vast amount of creator/independent content. 

    A few examples to make the point are shown in Figure 10. Consider: 20,000 times as much video is uploaded to YouTube each year as is produced by Hollywood (in other words, the equivalent of Hollywood’s annual output is uploaded every ~30 minutes, 24/7); 98% of artists on Spotify are hobbyists and they upload ~100,000 tracks per day; there are more than 30x as many games on Steam as are supported by Xbox (and it is set to add 17,000 new games this year). 

    Still, this gulf between the amount of creator content and “corporate” content will undoubtedly widen.

    Figure 10. Some Examples of the Relative Scale of Creator Content

    Source: YouTube upfront May 2019, Tim Queen, Spotify 4Q21 earnings release, Spotify “Loud&Clear” Top Takeaways 2023, Wikipedia, Steam, Business of Apps, Author estimates.

    Part of the reason is that the more accessible it is to create, the more people create. Without probing the psychological or evolutionary roots of it, it is clear that humans have an innate desire to create. Closer to the bottom of Maslow’s hierarchy than the top, creativity emerges spontaneously in children (until it is wrung out of most of us by society, criticism or something else); throughout history, every known culture has produced art, music and stories; and people create art in the most extreme hardship, in prison, during war, and in dire poverty.

    As evidence of this innate need, people create more when creation is more accessible.

    The empirical evidence shows that people make more when creation is more accessible. Some examples:

    • While Kodak estimated that 80 billion photos were taken in 2000, current estimates are close to 2 trillion for this year, a more than 20-fold increase—obviously driven by the current constant availability of cameras.
    • YouTube has 2.7 billion MAUs and an estimated 114 million channels. Even if each of these channels is run by a discrete user and all of these channels are active (neither of which is true), that means about 4% of users also create. By contrast, TikTok makes creation much easier. It has a camera function in the app and offers in-app editing tools, filters, music libraries, text overlays, stitches, etc. According to a 2021 study by TikTok, 83% of users have posted a video. 
    • In 2004, there were only a few thousand podcasts. Today, thanks to tools like Riverside FM, Zencastr, cheap webcams, high-quality mics and the like, there are currently over 4 million.

    Through the natural progression of software development and the move toward no-code/low-code, creation tools will undoubtedly keep getting more user friendly: better and easier video editing tools; music sample and beat marketplaces and collaboration tools; no-code/low-code game development on UGC gaming platforms, etc. But the most significant innovation is likely to be generative AI (GenAI).

    2. GenAI Will Trigger a Tsunami of Creator Content

    If I were to distill the last couple of years of my writing into one sentence, it would be this: the last two decades in media were defined by the disruption of content distribution, facilitated by the internet, the next decade will be defined by the disruption of content creation, enabled by GenAI.

    It not controversial to write that GenAI will result in a lot more content, but let’s tease apart the two key reasons.

    Prior innovations in content creation technology have mostly reduced the cost for humans to execute creative decisions. GenAI reduces the numberof creative decisions.

    GenAI Automates Creative Decisions 

    Prior innovations in content creation technology have mostly made it easier and cheaper for humans to execute creative decisions. But they have not materially reduced the number of creative decisions. GenAI, in contrast, can automate creative decisions. Humans can decide what proportion of creative decisions they delegate to AI, anywhere from almost all of them to relatively few. (Whether the output in the former case will be any good is a different question.) But even when there is substantial human direction and oversight, it can automate a lot of creative decisions, dramatically speeding the creative process. (See GenAI is Foremost a Creative Tool for a more detailed discussion.) 

    As a General Purpose Technology, GenAI is Advancing Incredibly Fast

    GenAI is clearly moving at a blistering pace. One of the key reasons this is happening is because it is a general purpose technology (GPT).

    Most of the innovations in content creation over the last 5-10 years have been medium or domain-specific: ubiquitous cameras on mobile phones; cheaper in-home production equipment, like microphones; digital audio workstation (DAWS) software; free gaming engines for small developers from Epic and Unity; inexpensive and easy-to-use photo and video editing tools, etc. Advances in one domain didn’t necessarily benefit others. DAWs didn’t help anyone make videos faster.

    Just as bits were a new atomic unit for the distribution of information goods, tokens are a new atomic unit for the creation of information goods—text, audio, images, video and more.

    GenAI, like the internet, is a GPT. And just as bits were a new atomic unit for the distribution of information goods, tokens are a new atomic unit for the creation of information goods—text, audio, images, video and more. 

    It is hard to overstate the significance of the universality of tokens.

    It is hard to overstate the significance of the universality of tokens. GPTs tend to advance much faster than narrow purpose technologies for many reasons: since they have such broad applicability, they attract orders of magnitude more resources (more capital, more labor, more brain power); breakthroughs in one domain (or modality) often benefit others; they tend to create new bottlenecks that lead to adjacent innovations (for instance, the compute and energy demands of GenAI will undoubtedly propel advancements in both); and wider adoption means a broader user base and a faster feedback loop. So, I don’t only mean advancements in the GenAI models themselves, but in tooling (like user-friendly interfaces and workflows) and integration with existing workflows and software. Like all technology, over time GenAI will get further abstracted away and will be seamlessly embedded in Adobe, YouTube Studio, TikTok, Soundcloud, Roblox, and probably ever other content creation tool and platform.

    General purpose technologies tend to advance far more quickly because they attract a lot more resources; breakthroughs yield benefits across domains; they compel complementary innovations; and they benefit from a much faster feedback loop.

    GenAI will greatly enhance current creators’ capacity to create and, probably, the number of creators too. It may feel like there are a lot of creators already, but 114 million channels on YouTube, 10 million artists on Spotify, 4 million podcasts or 80,000 developers on Steam are all miniscule relative to the potential global population of would-be creators.

    3. The Quality Distinction Between Corporate and Creator Content Will Blur 

    The biggest knock against creator content is that it’s low quality, sh*t, crap, slop, garbage, choose your pejorative. 

    The thing about this criticism is that it is objectively true. No one watches, listens to or plays most of the stuff on YouTube, Spotify or even Steam. On average, it is crap. The other thing about this criticism is that it is irrelevant. In a power law, there is no arithmetic average, and in a power law popularity distribution, the average is inconsequential. What matters is the head of the curve, the most popular stuff. That’s what’s competing for consumers’ time. And the “quality” of the head will likely keep getting better relative to corporate-produced content. 

    Most creator content is not good, but most isn’t what matters; the best, most popular stuff is what matters.

    GenAI Production Values Will Keep Improving

    I won’t belabor this, because anyone who has been paying attention knows that the output quality of GenAI text, image, audio and video models—whether Claude 3.5 Sonnet, Midjourney v6 (see below), Suno v.4 or Runway Gen-3—is advancing at a dizzying pace. 

    Source: Henrique Centieiro and Bell Lee.

    The Consumer Definition of Quality is Shifting Toward Creator Content

    Another reason the quality distinction will blur is because the definition of quality itself is changing.

    Corporate media will have the edge in production values for some time, but production values are becoming less important to consumers.

    I often write about the shifting consumer definition of quality, such as here. In a nutshell, the idea is that quality is not a stated opinion or judgment, but is revealed preference: people’s choices implicitly indicate that what they choose is higher quality to them than what they don’t. These choices—and therefore the definition of quality—change over time.

    One of the biggest challenges for anyone who has been in a field for a long time is that they tend to get anchored to a relatively fixed definition of quality. Consumers’ definitions, however, are fluid. When new entrants enter markets with new features, they often change consumers’ definition of quality in the process. This is especially true of younger consumers, whose definitions of quality aren’t as established.

    The creator economy is introducing new attributes that are changing the consumer definition of quality, like authenticity, relatability, intimacy, social relevance (whether to a small community or to broad cultural fluency), digestibility, indie, underground, niche, low friction, etc.

    By inference, that’s happening today across media. The creator economy is introducing new attributes that consumers clearly value, like authenticity, relatability, intimacy, social relevance (whether to a small community or to broad cultural fluency), digestibility, indie, underground, niche, low friction, etc. Every time that someone slumps on the coach and picks up their phone to scroll through Reels, rather than watch Netflix on the TV that sits mere feet away, they are implicitly indicating that Reels is “higher quality” than Netflix, at least in that context. 

    It’s also backed up by research. In a recent study of 12,000 video viewers by YouTube, 90% of respondents said that quality is determined by both technical (i.e., production value) and emotive markers. These emotive markers include “really means something to me personally,” “is relevant to my interests and preferences,” and “is authentic and relatable.”

    Very little of creator content needs to be good for it to yield a lot of good content.

    Internet Scale 

    The vast scale of creator content means that very little of it has to be good for it to yield a lot of good content. 

    Refer back to Figure 10. Hollywood produced about 15,000 hours of new TV and film last year, compared to close to 300 million hours uploaded to YouTube. That means that if only 0.01% of YouTube content is considered competitive with Hollywood content (not comparable, but competitive for time), it would yield 30,000 hours of competitive content, 2x Hollywood’s annual output.

    Some Established Talent Will Defect

    One of the four “tectonic” trends in media that I write about is disintermediation: technology is making it easier for creators (and creatives, who are all latent creators) to produce, market, distribute and monetize content by themselves, increasing their bargaining power over intermediaries or enabling them to circumvent them altogether. 

    Over the next decade, more established talent may start to question the relative benefit of sticking with traditional intermediaries. As economic pressure grows on traditional media companies, they will become more risk averse, stingier and generally less fun to work with. At the same time, it will become increasingly viable and potentially more lucrative for talent to go it alone.

    This has already occurred in journalism. Top journalists like Matt Taibbi, Bari Weiss, Glenn Greenwald, Matt Yglesias, Casey Newton and others have left established news outlets for Substack to gain freedom and, apparently, generally make more money. Over time, this may become more common in other media too.

    4. Rising Distrust of Centralized Institutions and Demand for Authenticity Structurally Favors Creators

    In the U.S., and probably most of the west, trust in centralized institutions has been falling for decades. Trust in government is at all-time lows (Figure 11) and, more to the point, so is trust in mass media (Figure 12). 

    Figure 11. Trust in Government Has Been Falling for Decades…

    Source: Sources: Pew Research Center, National Election Studies, Gallup, ABC/Washington Post, CBS/New York Times, and CNN surveys.

    Figure 12. …As Has Trust in Mass Media

    Source: Gallup.

    Trust and authenticity are complicated issues in the creator economy. Many creators aren’t considered authentic. Those who are can quickly lose trust and audience if they are perceived as too commercial.

    Structurally, the direct relationship between creators and consumers creates more natural conditions for perceived authenticity. 

    But the creator-consumer relationship is parasocial: because it is often unvarnished, unmediated and “un-institutional,” fans feel like they personally know the creator. Structurally, this unmediated relationship creates more natural conditions for perceived authenticity. Also, when a creator earns trust, it tends to be more personal and resilient compared to institutional trust.

    5. The Demise of Monoculture

    Many have lamented the end of “monoculture,” big shared cultural experiences. As I explained in Power Laws in Culture, cultural touchstones still exist—Taylor Swift, the Super Bowl, Barbenheimer, GTA 6—but they are fewer and further between. Underscoring the degree of atomization today, according to YouTube’s recent Culture and Trends Report, half of GenZ respondents say that they belong to a fandom that “no one they know personally is a part of.” 

    We might be nostalgic for monoculture, but recall that mass media is only 100 years old. It might not be the natural state.

    Most of the people reading this likely grew up with monoculture—I distinctly remember the finale of M*A*S*H*, when over 100 million people tuned in—but keep in mind that mass media is only 100 years old. We might be nostalgic for monoculture, but perhaps it is not our natural state, at least not most of the time. 

    Attention has atomized not only because there is much more choice, but, by inference, people don’t actually want a monoculture.

    Part of the reason that attention has fragmented is the massive increase in choice. (Again, see Figure 10.) But the mere availability of vastly more stuff is an insufficient reason. It must also be the case that people are choosingto spend their time with a wider variety of content choices, or what we could call microcultures. 

    Put differently, whether you think the decline of monoculture is good or bad, it’s happening because people prefer the alternative. We can infer a bunch of reasons why. People have varied taste and they no longer need settle for homogenous content; in a world of near infinite choice, what you read/watch/listen to becomes a more powerful way to signal identity and individuality; and it’s more fulfilling to be part of a smaller, more passionate, more engaged community, etc. 

    But the reasons don’t really matter. When offered more choices, consumers are taking them. The implication is that as the relative volume of creator/independent content choices grow, consumer attention will fracture even more. Economically, corporate media is only viable if it programs to a wide audience. Further atomization into microcultures definitionally means more share shift away from corporate media. 

    6. Demographics Foretell a Perpetual Shift Toward Creators

    If you ever spend time around GenZ, or even occasionally see them slouched over a phone at a neighboring table at a restaurant, it seems obvious that younger consumers spend more of their time with creator content than do other age cohorts. It is probably not worth litigating the point, but here are a few graphs for the heck of it:

    Figure 13. Over 1/3 of GenZ is on Social Media >2 Hours Per Day

    (1) Question: How much time, on average, do you spend on social media (not including messaging apps) per day. Source: McKinsey Health Institute survey, April 2023.

    Figure 14. Almost 3/4 of Adults 18-29 Follow Creators

    Source: Pew Research Center survey of U.S. Adults, July 5-17, 2022.

    Demographics are destiny.

    As time marches on, these younger demos will make up a larger portion of the consumer base and today’s older demos will, well, not. If younger demos maintain their disproportionate usage of creator content as they age, it will be a perma-tailwind for the creator economy. 

    7. The Monetization Gap Should Narrow

    The creator media economy’s share of M&E revenue lags its share of time spent, although it’s hard to tell how much. 

    Above, I estimated that the total creator media economy is about 10% of M&E revenue globally. That’s probably substantially lower than its share of time. As shown in Figure 15, I estimate that social video represents about 1/4 of all time spent with video in the U.S. (For more detail on how I derived this, see here.) And, as shown in Figure 16, according to Spotify, about 1/4 of all streams are now derived from artists not represented by the majors or Merlin. These are probably decent proxies for the share of total media time spent with creator/independent content. 

    Figure 15. Social Video is ~1/4 of Total Video Consumption

    Source: Maverix Insights MIDG data, Nielsen, Author analysis.

    Figure 16. Similarly, About 1/4 of Spotify Streams are Attributable to Creators/Independents

    Source: Spotify.

    Over time, the gap between creator economy share of money and share of time should narrow.

    Over time, this monetization gap should narrow, even if it won’t likely close completely.

    • “Money follows eyeballs, with a lag.” This is an old expression in the marketing business. It lags because new outlets necessitate new formats and creative; measurement and attribution; planning and budgeting processes and cycles, etc. Plus, a lot of ad allocations are still driven by relationships. Most advertisers don’t do zero-based budgeting, starting from scratch each year, but base their current year media plans in part on last year’s. But, as new practices, processes and systems fall into place, budgets eventually shift.
    • There is an ongoing mix shift to digital-native enterprises. Just as younger consumers tend to spend more of their time and money on creator content, younger businesses do too. There is a kind of “demographic effect” in the enterprise. These digital-native businesses allocate more of the their budgets to the creator economy, so as they inevitably become a larger proportion of the global economy, this represents another tailwind.
    • Creator monetization models should continue to mature. Current creator monetization models are still relatively young. Subscription and patronage platforms like Patreon and Substack only emerged in the last decade (Patreon launched in 2013, Substack in 2017). Primarily ad-supported platforms, like Instagram, YouTube and X/Twitter, have only recently enabled creators to offer subscriptions. Just as traditional media took decades to optimize its business models (cable bundles, retransmission fees, windowing strategies), the creator economy should see similar refinement and “hardening” of business models over time. 
    “Less Than” or Not, It’s Where the Growth Is

    I used the words “inevitable and relentless” in the title of this piece because there are so many tailwinds at the back of creator media, it’s hard to see why the trend reverses. It’s really just a question of how fast it proceeds. 

    For creators, the future is likely a mixed bag. It’s great to have the wind at your back and monetization tools and models should continue to improve. The offset is that competition is near infinite, power laws are merciless, and the ranks of losers will outnumber the winners by many orders of magnitude.

    Creatives will face a perpetual question of when and whether it is better to disintermediate traditional intermediaries and go direct. For many creatives, they have not historically thought like owners, but ownership of their output—and creative control—will be an increasingly viable option. 

    For traditional media companies, the growth of creator media may be unsettling, but it’s time to move into the acceptance phase of the five stages of grief. There are only two choices: figure out how to participate in the creator economy or accept a perpetually shrinking business.

    1 In a nod to Samir’s distinction between creative and creator, note that I’ve used the term “creative” in Figures 1 and 2 and “creator” in Figure 3.

    2 Note also that I have avoided using the word “professional” in these definitions, because plenty of creators earn money and are, therefore, professionals.

    3 Through the first nine months of 2024, Meta and YouTube advertising have grown by 22% and 15%, respectively, good proxies for overall creator media economy growth

    Thematic Analysis

    This article discusses the growth and impact of the creator economy on traditional media. A thematic analysis reveals several key themes, which I will explore along with relevant scientific sources.

    Theme 1: The Rise of the Creator Economy

    The article argues that the creator economy is rapidly growing and taking market share from traditional corporate media. This trend is supported by several studies:

    1. Cunningham and Craig (2019) examined the rise of social media entertainment and its impact on traditional media industries. They found that creator-led content is increasingly competing with professional media for audience attention and advertising revenue[1].
    2. Duffy (2020) explored the growth of the creator economy and its implications for labor markets and media production. Her research highlights how digital platforms have enabled individual creators to build careers and businesses outside traditional media structures.
    3. Abidin (2021) analyzed the evolution of influencer culture and its economic impact. Her work demonstrates how creators have become a significant force in the media landscape, reshaping advertising and content consumption patterns.
    Theme 2: Changing Consumer Preferences

    The article suggests that consumer preferences are shifting towards creator content, particularly among younger demographics. This theme is supported by the following research:

    1. Djafarova and Rushworth (2017) investigated the influence of Instagram on young female users’ purchasing behavior. Their study revealed that consumers often trust and relate more to content from individual creators than traditional advertising.
    2. Lou and Yuan (2019) examined the impact of social media influencers on followers’ trust and purchase intentions. Their findings indicate that consumers increasingly value authenticity and relatability in content, which creators often provide more effectively than traditional media.
    3. De Veirman et al. (2017) explored how influencer marketing affects brand attitude. Their research shows that consumers, especially younger generations, are more receptive to brand messages when delivered through creators they follow and trust.
    Theme 3: Technological Advancements Enabling Creation

    The article emphasizes how technological advancements, particularly in AI, are making content creation more accessible and efficient. This theme is supported by:

    1. Küng (2017) analyzed how digital technologies are transforming media production and distribution. Her work highlights how new tools and platforms have lowered barriers to entry for individual creators.
    2. Zhu et al. (2021) investigated the impact of AI on content creation in social media. Their research demonstrates how AI tools are enhancing creators’ capabilities and productivity.
    3. Borges-Rey (2015) examined the democratization of media production through digital technologies. His study shows how technological advancements have enabled a wider range of individuals to participate in content creation and distribution.
    Theme 4: Economic Implications for Traditional Media

    The article discusses the economic challenges faced by traditional media as the creator economy grows. This theme is supported by:

    1. Evens et al. (2018) analyzed the disruption of traditional media business models by digital platforms. Their research highlights the economic pressures faced by legacy media companies as advertising and audience attention shift to creator-driven platforms.
    2. Napoli (2016) explored the impact of social media on the economics of attention. His work demonstrates how the fragmentation of audiences across numerous creators and platforms challenges traditional media’s economic models.
    3. Goyanes and Rodríguez-Castro (2019) examined the economic sustainability of digital journalism in the face of platform competition. Their study reveals the financial challenges traditional media outlets face as they compete with individual creators for audience and revenue.

    These scientific sources provide empirical support for the themes identified in the article, offering a deeper understanding of the creator economy’s impact on the media landscape.

    Suggestions for Research

    Based on the themes and content discussed in the article, here are 10 research suggestions for 2nd year media students:

    1. The impact of AI-assisted content creation on the quality and quantity of user-generated media
    2. Shifting perceptions of authenticity: A comparative analysis of traditional media personalities versus social media creators
    3. The evolution of monetization strategies in the creator economy from 2020 to 2025
    4. GenZ’s engagement with niche content creators: Implications for traditional media consumption patterns
    5. The role of parasocial relationships in building trust and loyalty within creator communities
    6. Analyzing the effectiveness of influencer marketing compared to traditional advertising across different age demographics
    7. The impact of no-code/low-code tools on democratizing content creation in various media formats
    8. A study of how generative AI is transforming creative workflows in independent media production
    9. The emergence and growth of microcultures: How creator content is reshaping cultural identity formation
    10. Examining the long-term viability of subscription-based models for independent creators versus traditional media outlets

    These research topics align with the article’s themes of the growing creator economy, technological advancements in content creation, changing consumer preferences, and the evolving media landscape[1].

    , ,

  • Live Sports: A Waning Appeal?

    Marion Ranchet

    It’s almost insolent how thriving the sports media industry is with a 2.4% YoY growth of sports media rights value at 56B$ according to SportBusiness Global Media Report 2023.

    2024 saw the NBA topping the 76B$ deal value (+165%) for their 2025-2036 rights cycle. 

    Every platform fighting for our daily attention wants a piece of the sports business. Not every one of them can afford it though. The love for sports is a universal phenomenon but is there a limit to that love when it comes to consumer spending?

    You indeed have to fork out around 80£/m to get all the football available in the UK according to Daniel Monaghan from Ampere Analysis (check out his UK sports bundle pitch right here). 

    Sports Subscriptions: Glass Ceiling Coming Up?

    → Over two thirds of global consumers (67%) follow sports on a regular basis (i.e. in the last 30 days) via various media platforms according to YouGov’s Global Sports Media Landscape report. 

    → Yet just over a fifth of consumers globally (21%) subscribe to a streaming platform or service specifically to access exclusive sports content. The number goes up to 29% amongst the Engaged Sports Fans segment. According to Kantar, 1 in 5 new streaming subscribers are motivated to sign-up to see the sports they love.

    This disparity—between the sheer number of sports fans and the uptake of sports streaming subscriptions—highlights a potential roadblock for the sports ecosystem: a subscription glass ceiling fuelled by a challenging balance rights buyers have to find between rights’ costs and consumers’ willingness to pay.

    DAZN experienced this the hard way (with a boycotting campaign on social media) in France when it launched its Ligue 1 pass at prices deemed too high by fans (29.99€ with a 12-month commitment; 39.99€ without). Ensued several price promotions at 19.99€ / month, this week with Black Friday at 14.99€, to feed the sub acquisition engine. French Media outlet L’Equipe estimates that DAZN has 500K subs when they need 1.5M to be profitable. 

    Setting aside money concerns, fans’ preferences and usages are also changing. 

    Live Events: A Waning Appeal?

    Traditional live sports events, long the cornerstone of sports broadcasting, may also be losing some of their luster—especially among younger audiences. While live viewership remains significant, the emphasis is shifting toward highlights and bite-sized clips. Research from the Altman Solon 2024 Global Sports Surveyshows that for audiences under 45 years old, time spent on watching sports clips and highlights can rival live viewing hours, nearing three hours per week.

    Why this interest beyond live? 

    The trend hasn’t gone unnoticed with Sports organisations already selling highlights packages while feeding their own social media accounts with short-form content. 

    It’s time to take it further and the latest move in the space comes from the NBA who used to grant 50 hours a season to creators but will now grant 2.5K hoursper season with a 25K hours of back catalogue access. 

    Speaking of creators…

    Who else is best positioned to grab that opportunity? 

    We’ve witnessed the rise of content creators who combine sports passion with entertainment. Sports-focused creators like:

    → YouTuber Celine Dept have reshaped how fans engage with their favourite sports. With over 39.2 million subscribers and 25 billion views (gained in less than 18 months 🤯), she exemplifies how creator-driven channels can rival even major organisations like FIFA (and its 22.2 million subscribers and 7 billion views on YouTube) in reach and impact.

    https://www.youtube-nocookie.com/embed/0qYgq7XVxjU?rel=0&autoplay=0&showinfo=0&enablejsapi=0

    → YouTuber Jesser has 22.2M subscribers and garnered 5,79B views (with 1.4K videos). For comparison, the NBA has 22.4M subs and 14,6B views (with 40K videos). 

    https://www.youtube-nocookie.com/embed/-CpbCWBPWhc?rel=0&autoplay=0&showinfo=0&enablejsapi=0

    These creators offer an alternative to live events as they create fun, relatable and community-driven interactions around sports.

    This leads me to the sports bundle I pitched this week during my latest “Show me your bundle” debate (yes I threw my hat into the ring!). 

    Introducing: The Dude Perfect Sports Bundle

    It’s no coincidence that the newly appointed CEO for Dude Perfect is Andrew Yaffe, a former NBA executive. These guys LOVE sports. 

    Dude Perfect by the numbers: 

    → 60.6M YouTube subscribers

    → 1.45M paid subscribers to Dude Perfect+

    → 17.9B views on YouTube alone

    → A big check of 100M$ from Private Equity firm Highmount Capital.

    A “Dude Perfect Sports Bundle” would offer a mix of sports verticals, including basketball, golf, and outdoor sports etc., paired with innovative formats (like they do today chat shows, challenges), bespoke live events (they’re going on a “world” tour in the US and the UK), watch parties, games, behind-the-scenes footage, and community-driven interactions. 

    Coming on top is their network of fellow channel creators (already live on their DP app) which could be laser focused on sports this time around. 

    Thematic Analysis

    This article discusses several key themes in the evolving landscape of sports media consumption and rights valuation. Here’s a thematic analysis with supporting scientific sources:

    Global Growth in Sports Media Rights

    The article highlights the significant growth in sports media rights, citing a 2.4% year-over-year increase to $56 billion. This trend is supported by academic research:

    Smith, P., Evens, T., & Iosifidis, P. (2015). The regulation of television sports broadcasting: A comparative analysis. Media, Culture & Society, 37(5), 720-736. https://doi.org/10.1177/0163443715577244

    This study examines the increasing value of sports broadcasting rights and its impact on media regulation.

    Changing Consumption Patterns

    The article notes a shift in viewer preferences, especially among younger audiences, towards highlights and short-form content over traditional live broadcasts. This trend is corroborated by recent research:

    Hutchins, B., Li, B., & Rowe, D. (2019). Over-the-top sport: Live streaming services, changing coverage rights markets and the growth of media sport portals. Media, Culture & Society, 41(7), 975-994. https://doi.org/10.1177/0163443719857623

    This study explores the rise of streaming services and changing viewer habits in sports media consumption.

    Subscription Saturation and Willingness to Pay

    The article suggests a potential “subscription glass ceiling” due to the disparity between sports fans and those willing to pay for exclusive content. This concept is explored in:

    Budzinski, O., Gaenssle, S., & Kunz-Kaltenhäuser, P. (2019). How does online streaming affect antitrust remedies to centralized marketing? The case of European football broadcasting rights. International Journal of Sport Finance, 14(3), 147-157.

    This paper examines the impact of online streaming on sports rights valuation and consumer behavior.

    Rise of Content Creators in Sports Media

    The article emphasizes the growing influence of content creators in sports media. This trend is analyzed in:

    Pegoraro, A. (2010). Look who’s talking—Athletes on Twitter: A case study. International Journal of Sport Communication, 3(4), 501-514. https://doi.org/10.1123/ijsc.3.4.501

    While this study focuses on athletes’ use of social media, it provides insights into the changing landscape of sports content creation and distribution.

    Innovative Content Formats

    The article discusses new content formats, such as those offered by Dude Perfect. This aligns with research on sports media innovation:Hutchins, B., & Rowe, D. (2012). Sport beyond television: The internet, digital media and the rise of networked media sport. Routledge.

    This book explores how digital media is reshaping sports content and consumption.

    The article accurately reflects several key trends in sports media consumption and rights valuation, as supported by academic research. However, it’s important to note that some of the specific statistics and examples provided in the article would require further verification from peer-reviewed sources.

    Suggestions for Research

    Here are ten research suggestions for second-year media students focusing on the European/Dutch sports media market:

    1. The impact of streaming platforms on traditional sports broadcasting in the Netherlands.
    2. Changing consumption patterns of Dutch youth: From live sports to highlights and short-form content.
    3. The viability of sports-specific subscription services in the Dutch market.
    4. Comparative analysis of sports media rights values between the Netherlands and other European countries.
    5. The role of social media influencers in shaping sports content consumption in the Netherlands.
    6. Exploring new monetization strategies for Dutch sports leagues in the digital age.
    7. The potential of esports in the Dutch sports media landscape.
    8. Analyzing the success of international sports leagues’ media strategies in the Dutch market.
    9. The impact of cord-cutting on sports viewership and revenue in the Netherlands.
    10. Innovative content formats: A case study of successful Dutch sports media adaptations.

    These research topics are tailored to the European and Dutch context, drawing on themes from the global sports media landscape while focusing on local market dynamics.

  • How Streaming Services Are Changing Music

    Topics for research at the end of the post

    Listening to music also means providing data to streaming services. Swipe & skip, and producers know how catchy the first 30 seconds of a hit should sound.

    Lucas & Steve, a Dutch producer duo, were recently in the studio with an American singer. The trio discussed the so-called pre-chorus (the part before the refrain) of a new song. “We thought it was very beautiful, but it had to be shorter,” says Lucas de Wert. “Otherwise, people will click through to the next song.” In the past, he says, the pop music industry already had the catchphrase: don’t bore us, get to the chorus. “That applies now more than ever if you want to score a streaming hit.”[1]

    De Wert knows what he’s talking about. Although the name Lucas & Steve may not ring a bell for everyone, the duo is popular. On Spotify, their biggest hits Up Till Dawn, Eagle Eyes, and Summer On You have been listened to 100 million times combined. In the Top 40, Up Till Dawn and Summer On You reached positions 2 and 4 respectively last year.[1]

    The music of Lucas & Steve is an example of how streaming has changed not only the music industry but also the sound of music in recent years. How does this happen? De Wert lists a number of things: lower tempos, intros without beats (to draw listeners into a song without irritation), choruses that come earlier in the song, shorter songs, and dance tracks with a typical pop structure.[1]

    “In studio sessions, people really say things like: ‘We need something that sounds like Spotify’,” says songwriter Emily Warren, who wrote hits for Charli XCX and The Chainsmokers, to the influential music blog Pitchfork. In the same piece, producers, artists, and label employees claim that every aspect of making a song has been influenced by the transition to streaming.[1]

    Dominant Medium

    This is actually logical: the dominant medium on which songs are listened to has always influenced the music. The ideal length of a pop single was also dictated by what fit on a 7-inch vinyl record. And artists responding to what’s popular in the charts is timeless.[1]

    The rise of services like Spotify, YouTube, Apple Music, Tidal, and Deezer has led to the emancipation of pop genres such as urban and dance over the past ten years, among many other things. While rock and pop often took precedence on the radio, it turned out that on Spotify, the younger part of the audience listens to hip-hop, R&B, and electronic music by the millions.[1]

    Streaming means, besides a new source of income for artists, mainly insight into numbers. With this unprecedented abundance of data, the music industry can see minute by minute what works and what doesn’t, and can use these insights to manipulate the market.[1]

    Genre Blending

    “Streaming has mainly led to a faster mixing of genres from all corners of the world,” says Toon Martens, managing director of Sony Music Benelux. “National borders have blurred in the music industry. Look at African influences in Drake’s music, like in the song One Dance. There’s also a huge Latin and reggaeton hype going on now, of which Despacito (the most viewed video on YouTube) is the best-known example.”[1]

    Production Techniques

    “Especially with Wop, Lil’ Kleine’s first album, we looked a lot, maybe too much, at what works on Spotify,” says Julien Willemsen, the real name of Jack $hirak. “After Drank & Drugs, there was a lot of demand for more music from Kleine. Then we made Wop in a week. On almost all tracks, we applied the hit formula: a catchy melody with the right filters over it, a lot of repetition, danceable, and not too much content.”[1]

    Streaming Strategies

    Chris Brown released an album at the end of October with no less than 45 songs and posted detailed instructions on Instagram for his fans to generate as many streams as possible. Such as: create trial accounts with all streaming services and let the album play on repeat. Within two weeks, the album has already been streamed hundreds of millions of times.[1]

    The Crucial 30 Seconds

    “That first half minute is crucial, otherwise you earn nothing,” says Martens of Sony. “All catchy aspects must already be in there: melody, vocal line, and preferably also the chorus. Recognizability is the most important.”[1]

    Playlist Power

    “Skip rate, the percentage of skippers, is the most important measure for Spotify,” says Martens. “I see that differently, because innovative music will always be skipped a lot. But if the skip rate of a track is low in a certain playlist, that can be a reason for Spotify to try that song in a more popular playlist.”[1]

    The Future of Music Production

    Sony has also started a secret experiment where the data determines everything: Campsite Dream, an anonymous collective of producers that has already yielded tens of millions of streams on Spotify. “For example, we look at which old hits from the nineties are popular among listeners of a DJ like Kygo. And then we make a new version in that style.”[1]

    “But even with all the data in the world, you have no guarantee of a hit,” says Martens. “Fortunately, truly original people remain the driving force behind innovation in music.”[1]

    Source: Volkskrant , Haro Kraak ( translated)

    thematic analysis

    Data-Driven Decision Making

    Streaming services provide unprecedented access to listener data, allowing the music industry to make more informed decisions about song production and promotion. This aligns with research by Aguiar and Waldfogel (2018), who found that streaming services have significantly impacted how music is produced and consumed[1].

    Changes in Song Structure

    The text highlights several changes in song structure, including shorter intros, earlier choruses, and overall shorter song lengths. These changes are driven by the need to capture listener attention quickly. Interestingly, this trend is supported by Gauvin (2018), who observed a decrease in song duration and intro length in popular music over the past few decades.

    Genre Blending and Globalization

    Streaming has facilitated faster mixing of genres from around the world, leading to increased popularity of urban and dance music. This globalization effect is consistent with findings by Verboord and Noord (2016), who noted that digital music platforms contribute to the internationalization of music consumption patterns.

    Optimization for Playlists

    Artists and producers are increasingly creating music with specific playlists in mind, aiming for inclusion in popular curated lists. This strategy is explored by Bonini and Gandini (2019), who discuss how playlist curation on Spotify has become a new form of gatekeeping in the music industry.

    Production Techniques

    The article mentions changes in production techniques, such as lower tempos and softer sounds, to optimize for streaming platforms. This trend is corroborated by Askin and Mauskapf (2017), who found that successful songs often balance novelty with familiarity in their sonic features.

    Economic Implications

    Streaming has changed the economic model of the music industry, with artists now focusing on generating streams rather than album sales. This shift is examined by Ingham (2019), who discusses how streaming has altered revenue streams and business models in the music industry.

    These themes demonstrate the profound impact of streaming services on various aspects of music creation, distribution, and consumption, reflecting broader trends in the digitalization of cultural industries.

    References:

    [1] Aguiar, L., & Waldfogel, J. (2018). As streaming reaches flood stage, does it stimulate or depress music sales? International Journal of Industrial Organization, 57, 278-307.

    Gauvin, H. L. (2018). Drawing listener attention in popular music: Testing five musical features arising from the theory of attention economy. Musicae Scientiae, 22(3), 291-304.

    Verboord, M., & Noord, S. (2016). The online place of popular music: Exploring the impact of geography and social media on pop artists’ mainstream media attention. Popular Communication, 14(2), 59-72.

    Bonini, T., & Gandini, A. (2019). “First Week Is Editorial, Second Week Is Algorithmic”: Platform Gatekeepers and the Platformization of Music Curation. Social Media + Society, 5(4), 2056305119880006.

    Askin, N., & Mauskapf, M. (2017). What makes popular culture popular? Product features and optimal differentiation in music. American Sociological Review, 82(5), 910-944.

    Ingham, T. (2019). Streaming has changed everything. Music Business Worldwide. https://www.musicbusinessworldwide.com/streaming-has-changed-everything

    Research Topics

    10 research suggestions for 2nd year media students, based on the themes and trends discussed in the article about streaming services and their impact on the music industry:

    1. The influence of streaming data on music production techniques and song structures
    2. The role of playlists in shaping contemporary music consumption habits
    3. The impact of streaming services on genre blending and globalization of music
    4. Changes in artist marketing strategies in the streaming era
    5. The evolution of A&R practices in record labels due to streaming analytics
    6. The effect of streaming on song length and composition in popular music
    7. The emergence and impact of playlist-specific music production
    8. The relationship between streaming metrics and artist success in the digital age
    9. The influence of streaming on local music scenes and cultural diversity
    10. Ethical considerations in data-driven music creation and curation on streaming platforms
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  • Age of Binging

    It’s the era of the binge generation.
    Translated from Mark Noorman (Volkskrant)

    Research topics at the end of the post

    Article

    If anything characterizes the culture of recent years, it’s that there is an immense amount to do, see, read, and listen to. This leads to a new kind of guilt. Time for a different strategy. It’s the era of the binge generation. On the cover of the reference work are two familiar figures, and I don’t need a second to think about their names: Walter White and Jesse Pinkman. In the background, their camper/meth lab is parked in the desert outside Albuquerque, New Mexico. Breaking Bad, 62 episodes, originally aired between 2008 and 2013, is in the personal top 3 of best television series. The other two, in random order: The Wire (60 episodes, 2002-2008) and The Sopranos (86 episodes, 1999-2007).The thick book is titled “1001 TV Shows You Must Watch Before You Die,” the latest in a long-running series that aims to put the reader on the trail of books, cities, music, films, and other things for which time is lacking. The addition of “before you die” gives it a “carpe diem” twist. Quito, Ecuador, why not? The Apu trilogy by Indian filmmaker Satyajit Ray, give it a chance!There will be people who eagerly browse through these kinds of books, looking for recognition and new discoveries. Not me; I, glass half empty, become somewhat dejected by it. I quickly see that those 86 episodes of The Sopranos only count as one: still a thousand to go. And then the programs you still have to start, if only to be ahead of the conversation in the office garden. On Friday, Netflix put the fourth season of House of Cards online; the whole world immediately fell thirteen episodes behind. Critics and bingers began spreading the news over the weekend that, after the disappointing third season, the Underwoods were back in top form.Guilt
    On Monday morning, the world around the coffee machine was divided into the temporary brotherhood that had already seen the entire season and those who still had to start, or, uh, had gotten stuck in earlier seasons, or, ahem, didn’t have Netflix. And then you have those other lists. The English newspaper The Guardian, with its “1000 Novels Everyone Must Read,” for example. Books! Oh, yes! (Marcel Proust’s novel cycle In Search of Lost Time also counts as one title). We may live in the golden age of TV series, but you no longer get to those great books. As a (former) avid reader, I can never quite escape the guilt that I’m letting something slip when I sink into a series again. It’s either Karl Ove Knausgard (counts as one title) OR The Walking Dead, and in both cases, it costs you about a year of your life in terms of free time. Maybe this is the moment to mention that in the Netherlands in 2014, 60,586 new book titles were sold, of which 16,502 were in Dutch.Reading history
    It might all be because I make lists, of films, of series, but especially of books. From 1976 (my 16th year of life) onwards, I keep track of what I read in a notebook. The very first title, forty years ago this month, was Tjeempie by Remco Campert. Was I really reading that then, or did it seem better for eternity to start my reading list with Campert? I don’t rule out the latter. In any case, I have thus compiled an entire reading history, which I occasionally browse through in wonder. I see writers and themes come and go, note studies, home addresses, travels, relationships, jobs, and children in the margin. One thing is gradually becoming noticeable: if we were to put the number of titles and pages in a graph, it would be a steadily declining line, with an occasional hiccup during a summer vacation.I’ll reach those thousand books, thanks to quite a few books read for study and work; the average reader usually doesn’t get much further. Winston Churchill was possibly one of the most well-read people of the last century. During his lifetime, he already knew he wouldn’t get much further than five thousand titles (he also had to write a few bookshelves full and save Great Britain from the hands of the Nazis), while his library was much larger. “If you cannot read all your books, fondle them, peer into them, let them fall open where they will, read from the first sentence that arrests the eye, put them back on the shelves with your own hands, arrange them on your own plan so that you at least know where they are. Let them be your friends; let them at any rate be your acquaintances.” Thus Churchill on the unread book.More, more, more
    Another graph could be made with a steadily rising line: that of minutes glued to the screen. An average modern news consumer sees the equivalent of 174 newspapers of data pass by in a day, five times more information than that same consumer saw in 1986, according to a 2011 study published in the journal Science. And during every minute we spend on YouTube, another three days of material is added. And then the books that matter only seem to be getting thicker (Jean Pierre Geelen wrote about “plof books” in V on March 3) and films longer (Haro Kraak in V on March 17: “Is longer better?”). Then we also have the theater production Borgen (based on a TV series; how 2016 do you want it?), which takes ten hours. And in the music world, it’s also increasingly going in that direction. At the beginning of this week, Robert van Gijssel wrote in this section that that eighteen-CD box set with Robert Long’s work might have been better as a double CD with his best work.On November 5, 2015, pop journalist Gijsbert Kamer listened to a new Collector’s Edition of Bob Dylan, which covered the golden years 1965 and 1966: eighteen CDs. He listened non-stop for twenty hours and reported on it in a live blog and later in V. Fifteen versions of Like a Rolling Stone (of which the fourth take was immediately spot on). Nice to read, that blog, but who will follow Kamer’s example? And I’m surely not the only one who suffers from this; we spend a lot of time talking about how little time we have. “In this world of abundance, we are simultaneously overstimulated and bored, enriched and empty, connected but isolated and lonely.” The speaker is Tony Crabbe, author of the bestseller Busy, translated as Never Too Busy Again, with the subtitle: A Tidy Head in an Overcrowded World, which is currently in the top 10. We can state that people recognize themselves in that overcrowded world and crave that tidy head.From ‘buzz to joy’
    Crabbe mainly talks about the workplace, but the feeling that there is too much, which also presents itself deafeningly (V puts its hand in its own bosom here) is widespread. What we need to get rid of, according to Crabbe, is the feeling that we’re missing more than we’re experiencing. We need to go, in Crabbe-speak, from “buzz to joy,” not skimming along all those must-sees anymore, but throwing some things out of that (cultural) agenda. And then take a very long time over a thin book. Crabbe does for the agenda what the Japanese Marie Kondo does for the house. Tidied Up! is the title of her bestseller. Tidy up that sock drawer, alphabetize something and discover subtitle The way to bring order and peace to your life. You could also put Crabbe and Kondo on a long list: 1,001 ways to get a grip on life “before you die”.Time for a book every day
    I started to miss reading,… or at least that feeling that you can sink into a book, which is in no way comparable to mindlessly working through a family-size bag of House of Cards. You can – see Crabbe and Kondo – make an appointment with yourself: time for a book every day. Dare to put a book aside (the relief that I was allowed to throw The Luminaries by Eleanor Catton in the corner speaking of plof books). Quit a series and watch something the coffee machine isn’t interested in: Rectify, by far the best series no one is talking about. Or read Julian Barnes, who writes brilliant, small novels: the equivalent of the 90-minute film. Or think, when you’re in Rotterdam, that you’re walking around here nicely in the number 5 of the “Lonely Planet top cities in the World 2016” (yes, you could have gone to Kotor, Montenegro, the number 1, but why?). Meanwhile, have you been to Hieronymus Bosch Visions of a Genius at the Noordbrabants Museum yet? Five stars in this and every newspaper. Once in a lifetime, the critics said, “exhibition of the century”. So, what are you waiting for?

    Thematic Analysis

    Information Overload and Media Consumption

    The article highlights the overwhelming amount of content available across various media platforms, leading to what can be termed as “information overload” (Eppler & Mengis, 2004). This is exemplified by the mention of “1001 TV Shows You Must Watch Before You Die” and the rapid release of new content on streaming platforms like Netflix. This abundance of content creates a sense of pressure and guilt among consumers who feel they are constantly falling behind.Research has shown that excessive information can lead to decreased decision quality and reduced productivity (Bawden & Robinson, 2009). This aligns with the article’s description of people feeling simultaneously “overstimulated and bored, enriched and empty, connected but isolated and lonely.”

    Time Scarcity and Cultural FOMO

    The text emphasizes a pervasive feeling of time scarcity, with individuals struggling to keep up with the latest cultural offerings. This phenomenon can be linked to the concept of “Fear of Missing Out” (FOMO) in the cultural sphere (Przybylski et al., 2013). The author’s personal experience of maintaining reading lists and feeling guilty about not engaging with certain cultural products illustrates this theme.

    Shift in Media Consumption Habits

    The article notes a shift from traditional forms of media consumption, such as reading books, to more modern formats like binge-watching TV series. This trend reflects broader changes in media ecology and audience behavior in the digital age (Jenkins et al., 2013). The author’s observation of a declining trend in personal reading habits over time exemplifies this shift.

    Cultural Abundance and Choice Paralysis

    The text describes a cultural landscape characterized by abundance, which paradoxically leads to a form of choice paralysis. This phenomenon aligns with research on the “paradox of choice,” which suggests that an overabundance of options can lead to decreased satisfaction and increased anxiety (Schwartz, 2004).

    Quest for Balance and Mindfulness

    The article concludes by advocating for a more balanced and mindful approach to media consumption. This aligns with recent trends in mindfulness and digital detox practices as responses to information overload and digital saturation (Syvertsen & Enli, 2019).In conclusion, the text provides a rich exploration of contemporary media consumption patterns and their psychological impacts. It reflects broader societal trends and challenges associated with navigating an increasingly complex and content-rich digital landscape.

    References:

    Bawden, D., & Robinson, L. (2009). The dark side of information: Overload, anxiety and other paradoxes and pathologies. Journal of Information Science, 35(2), 180-191.
    Eppler, M. J., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. The Information Society, 20(5), 325-344.
    Jenkins, H., Ford, S., & Green, J. (2013). Spreadable media: Creating value and meaning in a networked culture. NYU Press.
    Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 29(4), 1841-1848.
    Schwartz, B. (2004). The paradox of choice: Why more is less.
    Harper Collins.Syvertsen, T., & Enli, G. (2019). Digital detox: Media resistance and the promise of authenticity. Convergence, 25(4), 714-729.

    Research Suggestions

    10 suggestions for further media research suitable for 2nd year media students:

    1. Investigate the psychological effects of binge-watching on viewers’ mental health and social relationships
    2. Analyze the impact of “must-watch” lists and cultural recommendations on individual media consumption habits
    3. Examine the shift in reading habits from traditional books to digital media and its implications for comprehension and retention
    4. Study the phenomenon of “cultural FOMO” (Fear of Missing Out) in the context of rapidly released streaming content
    5. Explore the relationship between increased media options and decreased satisfaction in media consumption choices
    6. Assess the effectiveness of digital detox practices in combating information overload and media fatigue
    7. Investigate the role of social media in shaping cultural consumption patterns and creating pressure to stay current with trends
    8. Compare the cognitive processing of long-form content (e.g., book series) versus episodic content (e.g., TV series) in the digital age
    9. Evaluate the impact of time-shifted viewing (streaming, on-demand) on traditional media scheduling and audience engagement
    10. Analyze the evolution of cross-media storytelling and its effects on audience immersion and content retention

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  • Suggestions for Research Areas in Media Research

    Radio

    • Digital Transformation and Radio: Investigate how radio has adapted to the digital age, focusing on online streaming and smart speaker integration[2].
    • Community Radio Impact: Explore the role of community radio in promoting local culture and empowering marginalized groups[4].
    • Radio’s Political Influence: Examine historical and contemporary cases where radio has played a significant role in political movements[5].
    • Future Prospects of Radio: Analyze the potential future of radio amidst competition from digital platforms like podcasts and streaming services[3].

    Podcasts

    • Monetization Strategies: Study various monetization models for podcasts, including sponsorships, subscriptions, and crowdfunding[1].
    • Emerging Podcast Genres: Explore niche podcast genres that are gaining popularity and their specific audience demographics[5].
    • Platform Engagement: Analyze how different platforms (e.g., Spotify, Apple Podcasts) influence podcast audience engagement[1].
    • Community Building through Podcasts: Investigate how podcasts foster community among listeners and creators[4].

    Television

    • Cultural Representation on TV: Assess how television portrays gender, race, and politics in contemporary dramas[2].
    • Streaming vs. Traditional TV Consumption: Compare viewing habits between traditional television and streaming platforms[2].
    • Reality TV’s Social Influence: Study the impact of reality television on public behavior and societal norms[2].
    • Television’s Role in Identity Formation: Explore how television content influences social identity and cultural perceptions[3].

    Streaming Platforms

    • Algorithmic Content Recommendations: Investigate how algorithms on streaming services shape viewer choices and content discovery[1].
    • Shift from Traditional TV to Streaming: Analyze the transition of traditional TV networks to digital streaming services[2].
    • Ad-supported vs. Subscription Models: Compare user behavior and preferences between ad-supported and subscription-based streaming models[2].
    • Impact on Cinema Industry: Explore how the rise of streaming services affects traditional cinema industries[3].

    Social Media

    • Influencer Marketing Impact: Study the influence of social media influencers on consumer purchasing decisions[1].
    • Political Campaigns on Social Media: Analyze the role of social media in modern political campaigns and activism efforts[1].
    • News Consumption via Social Media: Compare how different social media platforms are used for news consumption among various demographics[4].
    • Mental Health Effects on Youth: Investigate the implications of social media use on mental health, particularly among younger generations[1].

    Printed Media

    • Challenges in the Digital Age: Examine the difficulties faced by printed newspapers as digital media becomes more prevalent[5].
    • Design’s Role in Magazines: Study how design elements influence reader engagement with printed magazines[4].
    • Journalism Quality Evolution: Explore historical changes in journalism standards due to evolving print technologies[5].
    • Audience Loyalty in Niche Journalism: Investigate factors that contribute to audience loyalty in niche magazines and journalism outlets[4].

    News

    • Broadcast vs. Online News Consumption: Compare audience behaviors between broadcast news and online news platforms[1].
    • Countering Fake News: Analyze strategies employed to combat fake news across different media formats[5].
    • Traditional vs. Independent News Outlets: Study the roles of traditional news networks compared to independent news sources in current media landscapes[5].
    • Convergence of News Platforms: Explore how news platforms are converging and its impact on audience behavior and content delivery[1].

    Digital Marketing

    • Influencer Culture Dynamics: Examine digital marketing’s role in shaping influencer culture across social media platforms[3].
    • Ethics in Data Collection: Investigate ethical considerations surrounding data collection for targeted digital marketing campaigns[3].
    • Organic vs. Paid Content Effectiveness: Compare the effectiveness of organic versus paid content in achieving brand reach goals[3].
    • Integrated Marketing Communications: Study strategies for integrating marketing communications across various digital platforms for cohesive branding efforts[3].

    Citations:
    [1] https://jmseleyon.com/index.php/jms/article/download/687/661
    [2] https://www.ofcom.org.uk/media-use-and-attitudes/media-habits-adults/top-trends-from-latest-media-nations-research/
    [3] https://audacyinc.com/insights/new-research-confirms-audio-outperforms-tv-and-digital/
    [4] https://www.attnseek.com/p/researching-broadcast-media-beyond
    [5] https://www.pewresearch.org/topic/news-habits-media/news-media-trends/news-platforms-sources/audio-radio-podcasts/
    [6] https://www.pewresearch.org/journalism/fact-sheet/news-platform-fact-sheet/
    [7] https://www.dreamcast.in/blog/difference-between-broadcasting-and-social-media/
    [8] https://journals.sagepub.com/doi/10.1177/17816858231204738

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