Chapter 34: Further Reading

The Creator Economy: When the Algorithm Becomes Your Boss

1. Duffy, B. E. (2017). (Not) Getting Paid to Do What You Love: Gender, Social Media, and Aspirational Work. Yale University Press.

A landmark analysis of the labor dynamics of social media content creation, focusing particularly on women in the influencer economy. Introduces the concept of "aspirational labor" — the ongoing, often uncompensated work of building and maintaining a creator identity and audience — and documents how this labor is gendered in ways that reproduce existing inequalities. Essential reading for understanding the ideological dimensions of creator work.

2. Duffy, B. E., & Wissinger, E. (2017). Mythologies of creative work in the social media age: Fun, free, and "just being me." International Journal of Communication, 11, 4652-4671.

Examines the ideological narratives surrounding creative work on social media, identifying the myths of autonomy, fun, and authenticity that obscure the labor conditions and power dynamics of creator work. Documents how these mythologies are both genuinely experienced by some creators and systematically manipulated by platforms and brands.

3. Cunningham, S., & Craig, D. (2019). Social Media Entertainment: The New Intersection of Hollywood and Silicon Valley. New York University Press.

A comprehensive analysis of the social media entertainment ecosystem, examining how creator economy economics, platform governance, and cultural production interact. Provides detailed documentation of creator revenue structures, platform relationships, and the industry ecosystem that has grown around creator work.

4. Bishop, S. (2018). Anxiety, panic and self-optimization: Inequalities and the YouTube algorithm. Convergence, 24(1), 69-84.

One of the first academic studies to document creator anxiety specifically related to algorithmic opacity and volatility. Based on interviews with YouTube creators, it identifies how uncertainty about algorithmic systems produces specific psychological responses and shapes content production decisions. Essential for understanding the psychological dimensions of creator-algorithm relationships.

5. Mears, A. (2020). Very Important People: Status and Beauty in the Global Party Circuit. Princeton University Press.

Although focused on high-end nightclub and party culture rather than social media, this book provides essential conceptual tools for understanding the economics of attention, status, and appearance that underlie the creator economy. The analysis of how beauty and social capital are converted into economic value has direct applications to influencer economics.

6. Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52(1), 397-422.

The foundational review of occupational burnout research by Christina Maslach, the psychologist who developed the most widely used burnout framework. Provides the theoretical basis for applying burnout analysis to creator populations and explains the three dimensions of burnout (exhaustion, cynicism, inefficacy) and the organizational conditions that produce them.

7. Influencer Marketing Hub (2022). The Creator Economy: Benchmarks and Trends. Influencer Marketing Hub.

An annual industry report documenting creator economy scale, income distribution, platform economics, and emerging trends. While published by an industry organization with commercial interests, it provides the most comprehensive publicly available data on creator economy economics. Essential for understanding scale, income distribution, and platform-specific economics.

8. Shapiro, A., & Aneja, U. (2019). The Missing Middle: Aligning the Creator Economy. Omidyar Network.

An analysis of the "missing middle" of the creator economy — creators who are successful enough to have substantial audiences but not successful enough to have the business infrastructure and support that top-tier creators enjoy. Identifies the structural factors that constrain mid-level creator sustainability and proposes interventions.

9. Hearn, A. (2008). "Meat, mask, burden": Probing the contours of the branded "self." Journal of Consumer Culture, 8(2), 197-217.

An early and still influential analysis of self-branding as a labor practice, examining how the logic of brand management is applied to personal identity in the attention economy. Provides theoretical grounding for understanding the relationship between platform self-presentation requirements and personal identity.

10. Center for Countering Digital Hate (2020). Malgorithm: How Instagram's Algorithm Publishes Misinformation and Hate to Millions. CCDH.

Documents how Instagram's recommendation algorithm amplifies extremist and hateful content, with specific attention to how these dynamics affect different creator communities. While focused primarily on misinformation rather than creator economics, the research on disparate algorithmic amplification across demographic groups is essential for understanding creator equity.

11. Terranova, T. (2000). Free labor: Producing culture for the digital economy. Social Text, 18(2), 33-58.

A foundational essay in the political economy of digital media, examining how user-generated content constitutes a form of free labor that creates value for platform companies while being treated as leisure activity. Provides the conceptual framework for understanding creators as laborers whose work is obscured by the leisure-work boundary that platforms cultivate.

12. Gillespie, T. (2018). Custodians of the Internet: Platforms, Content Moderation, and the Hidden Decisions That Shape Social Media. Yale University Press.

The most comprehensive academic analysis of content moderation, examining how platforms make decisions about what content is allowed, how those decisions are implemented, and what the consequences are for users and creators. Essential for understanding demonetization dynamics and the governance structures that affect creator income.

13. Roberts, S. T. (2019). Behind the Screen: Content Moderation in the Shadows of Social Media. Yale University Press.

Documents the human labor that underlies automated content moderation systems, with attention to the psychological cost for human reviewers and the systematic limitations of moderation at scale. Provides important context for understanding why demonetization decisions are both systematic and inconsistent — the product of both automated and human systems operating under severe resource constraints.

14. Katz, L. F., & Krueger, A. B. (2019). The rise and nature of alternative work arrangements in the United States, 1995-2015. ILR Review, 72(2), 382-416.

A comprehensive labor economics analysis of the growth of alternative work arrangements — gig work, independent contracting, on-call work — in the United States. Provides the labor economics context for situating creator work within broader trends in the casualization of employment and the weakening of employment protections.

15. Donath, J. (2020). The Social Machine: Designs for Living Online. MIT Press.

An analysis of how digital platforms shape social interaction, with specific attention to how design choices create particular social dynamics and power relationships. Provides conceptual tools for understanding how platform design shapes creator-audience relationships and the parasocial dynamics that characterize creator work.

16. Taylor, T. L. (2018). Watch Me Play: Twitch and the Rise of Game Live Streaming. Princeton University Press.

A case study of the Twitch streaming platform and the live streaming creator economy, with detailed analysis of how streaming communities form, how streamers build and maintain audience relationships, and how the platform's business model shapes creator labor. Essential for understanding a creator economy context where parasocial labor is particularly central.

17. Crain, M. (2014). The limits of transparency: Data brokers and commodification of consumer information. Journal of Information Policy, 4, 456-482.

Examines how data on user behavior is commodified within the digital advertising ecosystem, providing essential context for understanding the advertising revenue systems that fund the creator economy. Helps explain why creator income is tied to the advertising market and what the structural implications of that dependency are.

18. Neff, G. (2012). Venture Labor: Work and the Burden of Risk in Innovative Industries. MIT Press.

An analysis of how risk is transferred from employers to workers in innovative industries, with the concept of "venture labor" — workers who take on financial and career risk in exchange for potential upside. Provides a powerful framework for understanding creator economy labor, where creators accept substantial financial precarity in exchange for the possibility of outsized returns.