Folk Theory: How do Content Creators Respond to Platform Algorithms?

by Yin Liang, Lecturer, Newcastle University Business School, UK

3 min read

Social media users and content creators are experiencing rapid growth at an astonishing pace. According to 2022 statistics, TikTok leads mobile app rankings with 672 million downloads, influencing over 150 million Americans. Globally, there are over 200 million content creators, with 43.7% being full-time creators. Additionally, 44% of creators rely on their creative income as the primary source of household revenue.

In the context of online content creation, visibility is the main "currency", symbolising both status and wealth. By extending their visibility on social media, content creators do not only receive financial rewards, but also influence broader political and soci(et)al issues. Taking YouTube as an example, as of 2022, 83% of YouTubers believe that YouTube has increased their income and has had a positive impact on their careers. Additionally, 83% of YouTubers express a desire to use their influence to positively impact society. As a result, gaining greater visibility has become pivotal for most online content creators.

On digital platforms, visibility is determined by ‘opaque’ algorithms. Since platforms rarely disclose detailed information about their algorithms, content creators use publicly-available, visibility-related metrics (e.g., number of video plays) to understand algorithms in a reverse way, thus creating or disseminating unsubstantiated "folk theories". Based on their understanding of these folk theories, content creators try to manipulate algorithms to influence visibility, and therefore feel more confident that they are outperforming others (regardless of whether this is actually true or not).

Most of these folk theories are based on the habits and intuitions of content creators, and therefore ambiguity characterises these folk theories. Importantly, the process of formulating and developing these folk theories is very fragile. Platforms themselves are seen as authoritative interpreters of their own algorithms. Once platforms publish information that essentially contradicts a given folk theory, then it simply falls apart. Therefore, while content creators may have mastered the craft of developing folk theories, manipulating algorithms is not an easy task. In fact, content creators are at the mercy of the platforms' algorithms.

In addition, folk theories are formed based on an overwhelming trust in the scientificity of algorithms. Excessive trust in algorithms and inaccuracies in folk theories can lead content creators to make wrong decisions when faced with wrong algorithmic results. However, even if they are disappointed with the unexpected results of the algorithm, content creators do not exit the platform easily, but continue to use it for different motives.

The non-transparency and complexity of algorithms imply that the emergence and development of folk theories is based on an after-the-fact understanding of algorithms and is not accurate. Folk theories do not represent a strong power for content creators against platforms, and the neoliberal ideology of virtual communities is merely a cover for algorithmic exploitation. Content creators do not really resist algorithmic control, and attempts at so-called algorithmic manipulation fall apart when confronted with the absolute authority of the platform.


About the Author

Dr. Yin Liang is a Lecturer at Newcastle University Business School. She did her PhD in Management at Durham University Business School (with Durham Doctoral Scholarship, funded by Durham University Business School). Yin is interested in work and employment in the context of the digital economy, the job quality of workers involved in those work configurations, and the impact of new technologies on these workers. Her research has been published in the Journal of Management Studies and New Technology, Work and Employment.

Technology, Employment and Wellbeing is a new FES blog that offers original insights on the ways new technologies impact the world of work. The blog focuses on bringing different views from tech practitioners, academic researchers, trade union representatives and policy makers.

picture alliance / ASSOCIATED PRESS | Bebeto Matthews

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