平台推荐逻辑是否塑造了公众对运动健康内容的参与？来自抖音和哔哩哔哩的400个视频证据
Do platform recommendation logics shape public engagement with sports health content? 400-video evidence from Douyin and Bilibili.
摘要(中文译文)
数字视频平台并非中立的渠道；其排名信号和界面塑造了什么内容能够被看见并具有价值。羽毛球——兼具观赏性与教学性——为比较抖音以互动优化为导向的短视频与哔哩哔哩以社区和知识为导向的生态提供了切入点。旨在考察不同平台原生发现环境中的互动模式是否存在差异，并通过算法文化过滤（algorithmic cultural filtering）视角对这些差异进行解读。我们使用各平台的原生发现顺序，分析了2025年6月抽样的400条视频（每个平台200条）；编码员记录了内容类型、创作者身份、视频时长及公开计数指标（点赞、评论、分享和收藏），编码者间信度极佳（κ = 0.94）。由于互动指标呈高度右偏分布，跨平台差异首先采用双尾Mann-Whitney检验并计算效应量进行考察。随后，我们对对数转换后的互动结果估计了多变量线性回归模型，并调整了平台、内容类型、视频时长、创作者身份和关键词匹配等变量。抖音产生显著更高的即时反应（点赞/评论/分享），而收藏/书签在平台间趋于一致；哔哩哔哩拥有更长的视频和更多的教学内容，且创作者生态存在分化（抖音以关键意见领袖为主导，哔哩哔哩以业余创作者为主导）。这些规律与算法文化过滤视角相一致，平台架构、创作者适应和受众偏好共同塑造了可见的互动模式。桥接形式（例如将精彩片段与模块化教学相链接）可能将注意力与学习连接起来。
Abstract
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. To examine whether engagement patterns differ across platform-native discovery environments and to interpret these differences through an algorithmic cultural filtering lens. 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 -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. 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.
如何引用
AMA
Zhao Zhang, Bing Shi. Do platform recommendation logics shape public engagement with sports health content? 400-video evidence from Douyin and Bilibili.. Frontiers in public health. 2026; doi:10.3389/fpubh.2026.1801241.
APA
Zhao Zhang, Bing Shi (2026). Do platform recommendation logics shape public engagement with sports health content? 400-video evidence from Douyin and Bilibili.. Frontiers in public health. https://doi.org/10.3389/fpubh.2026.1801241
GB/T 7714
Zhao Zhang, Bing Shi. Do platform recommendation logics shape public engagement with sports health content? 400-video evidence from Douyin and Bilibili.[J]. Frontiers in public health, 2026 doi:10.3389/fpubh.2026.1801241.
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