Business & Information Systems Engineering

Document Type

Research Paper


Content creators generate and upload content on social media platforms. If these platforms have a revenuesharing policy, content creators earn income from advertising revenue. This income is heavily dependent on the distribution of the content and the resulting view counts. Platform owners may exert algorithmic control that impacts content distribution, advertising income, and, consequently, the behaviour of content creators. The objectives of the platform owners combined with the interests of the content creators may lead to paradoxical tensions between the aims of control and autonomy. The opaque nature of algorithms coupled with the need to be recognised by the algorithm further reinforces this phenomenon. This study follows an interpretive qualitative research approach applying grounded theory methodology. This research uses semi-structured interviews with content creators to develop a theory explaining the tension between control and autonomy on revenue-sharing social media platforms. The study shows that algorithmic control and incentivisation create paradoxical tensions that affect the autonomy of content creators. Content creators attempt to minimise tensions of algorithm versus audience, regularity versus scheduling autonomy, and analytics versus decisionmaking autonomy in two ways: through self-centred measures such as improving metrics, pre-production, and being a pioneer and extraneous measures involving their own businesses, products, and sponsorships. This study sheds some light on the phenomenon of paradoxical tensions and provides guidance and strategies for content creators and platform owners about proceeding with their relationship. This study’s findings provide platform owners and decision- makers with a deeper understanding of the behaviour of content creators and the hurdles they face in platform work. The findings help them identify challenges, draw conclusions, and implement changes.