Background Digital video platforms are not neutral conduits; their ranking signals and interfaces shape what becomes visible and valuable. Badminton—balancing spectacle and instruction—offers leverage to compare Douyin's engagement-optimized short video with Bilibili's community- and knowledge-oriented ecology. Objective To examine whether engagement patterns differ across platform-native discovery environments and to interpret these differences through an algorithmic cultural filtering lens. Methods We analyzed 400 videos sampled in June 2025 (200 per platform) using each platform's native discovery orders; coders recorded content type, creator identity, duration, and public counters (likes, comments, shares, and bookmarks), with excellent inter-coder reliability (κ = 0.94). Because engagement metrics were highly right-skewed, cross-platform differences were first examined using two-tailed Mann–Whitney U -tests with effect sizes. We then estimated multivariable linear regression models for log-transformed engagement outcomes, adjusting for platform, content type, video duration, creator identity, and keyword match. Conclusion Douyin yields markedly higher instantaneous reactions (likes/comments/shares), whereas favorites/bookmarks converge across platforms; Bilibili hosts longer videos and more instructional content, and creator ecologies diverge (Douyin KOL-led, Bilibili amateur-led). These regularities are consistent with an algorithmic cultural filtering lens, with platform architectures, creator adaptation, and audience preferences jointly shaping visible engagement patterns. Bridge formats (e.g., linking highlights to modular instruction) may connect attention with learning.
Zhang et al. (Thu,) studied this question.