Frame by fame: Content creation on short video-format platforms

Problem definition: Short video-format platforms like NetEase and TikTok are attention economies that host User-Generated Content, in the form of combined video and audio elements, and operate on principles of network virality. This study explores user content creation strategies by focusing on decisions around content release frequency and the incorporation of adopted content in newly generated creations. Methodology/results: We theoretically explore the role of the following three mechanisms influencing these decisions: (a) Social hierarchies in the platform's network structure, (b) Virality of content on the platform, and (c) Algorithmic interventions through the ranking of content recommendations. To empirically study these relationships, we use a detailed log of user activity on NetEase Cloud Village registered during the month of November 2019 and carry out regression-based analyses. We find that high-status users, measured through their follower count, adapt their content release frequency strategically, slowing down after successful content to avoid dilution of potential virality. We also observe that high-status users generally deviate from prevailing viral trends in their content creation. However, following exceptionally successful releases, they tend to conform more to viral content, suggesting a risk-averse approach. Finally, contrary to algorithm aversion, users prefer content recommended by the platform. However, high-status users disregard algorithms to retain agency in decision-making. Managerial implications: Our findings provide a holistic understanding of the content creation process and suggest that platforms could strategically adjust algorithmic ranking policies to foster content creation diversity while catering to the preferences of users with different status levels.