The supply-side consequences of popularity signals: evidence from a natural experiment

Purpose This study investigates the supply-side consequences of disclosing popularity information on digital content platforms, focusing on how public disclosure of popularity metrics shapes creators’ production strategies along both the intensive margin (output volume) and extensive margin (thematic diversity). Design/methodology/approach We exploit a two-sided, platform-wide natural experiment on a major Chinese blogging platform that publicly displayed article view counts on December 7, 2020, and reversed the policy on February 5, 2021. Using a uniform random sample of 10,000 creators, we estimate the causal effect of disclosure with a DID-in-time design grounded in feedback intervention theory (FIT). We use the policy reversal as a reverse-shock test, conduct heterogeneity analyses by creator rank and niche density to examine FIT’s task-motivation and task-learning channels and construct a platform-level HHI to assess whether creator-level diversification is accompanied by aggregate topical concentration. Findings The public disclosure of popularity information significantly increases creators’ weekly output and thematic diversity. Notably, the increase in output volume is modest, whereas the expansion in thematic diversity is substantial, suggesting creators primarily respond by diversifying their content. These effects are robust across multiple empirical checks, including the reverse-shock analysis. Heterogeneity analyses reveal a cross-pattern consistent with FIT’s dual-channel architecture: the volume response is concentrated among low-rank creators (task-motivation channel), while the diversity response is concentrated among thin-niche creators (task-learning channel). Platform-level HHI shows no detectable increase during the disclosure period, indicating creator-level broadening does not translate into aggregate homogenization in our window. Originality/value This study uncovers a supply-side mechanism through which popularity signals influence creator behavior and extends FIT to the context of the creator economy. The findings demonstrate that popularity information functions as dual-purpose feedback by motivating higher output while guiding diversification, thus offering important implications for platform governance and the design of feedback systems.