讲座题目：From “Me” to “We”: The Effect of a Gamified Community Leaderboard on User Content Generation （从“我”到“我们”：游戏化社区排行榜对用户内容生产的影响）

主讲人：唐闯  北京大学汇丰商学院

时间：2025年10月15日15:00

地点：学院419

邀请人：曾伏娥

讲座摘要：

While the literature on user-generated content (UGC) has focused on incentive designs that motivate content creation through individual achievement and recognition, community-centric designs that leverage collective motivation are understudied. To address this gap, this study investigates how a gamified community leaderboard affects user content creation. We leverage a natural experiment from a leading social media platform in China that introduced a leaderboard for its superstar communities, allowing a randomly selected subset of users to earn points through content creation and contribute them to their community’s ranking. Using a difference-in-differences research design, we find that the leaderboard significantly increased the volume of both original posts and comments. This quantity increase was accompanied by a striking asymmetric effect on quality: while comment quality declined significantly, the quality of original posts remained unchanged. This suggests that users strategically preserve quality for highly visible content that represents their community while compromising on less prominent contributions. A causal forest analysis further reveals that the treatment effects are stronger for users with a stronger social identity and exhibit a U-shaped relationship with community size. Our findings provide important implications for designing effective community engagement strategies on UGC platforms.

现有关于用户生成内容（UGC）的研究主要关注通过个人成就与认可来激励内容创作的机制，而基于社区集体动机的设计则鲜有探讨。为填补这一研究空白，本研究考察了游戏化社区排行榜对用户内容创作的影响。我们利用一家中国领先社交媒体平台的自然实验：该平台为其超级明星社区引入了排行榜，随机选取部分用户，使其能够通过创作内容获取积分，并将积分贡献到所在社区的排名中。采用双重差分研究设计，我们发现排行榜显著提升原创帖子和评论的数量。这一数量增长伴随着质量上的明显不对称效应：评论质量显著下降，而原创帖子的质量保持不变。这表明用户在内容生产中存在策略性选择：他们会为代表社区的高曝光度内容维持质量，而在不那么突出的贡献上则有所妥协。进一步的因果森林分析显示，处理效应在社会认同感更强的用户中更为显著，并且与社区规模呈现U型关系。研究为UGC平台制定有效的社区参与策略提供了重要启示。

主讲人简介：

唐闯，北京大学汇丰商学院市场营销学助理教授，博士毕业于新加坡国立大学市场营销系。研究方向包括数字营销、平台经济、人工智能、多元化、公平与包容（DEI），善于运用因果推断方法、结构模型和田野实验。研究成果发表在Marketing Science和Information Systems Research等顶级学术期刊上。研究项目获得国家自然科学基金与广东省自然科学基金资助。论文曾获得多个学术会议最佳论文奖。教学兴趣包括平台经济、市场研究和定价策略，曾在毅伟商学院案例库（Ivey Publishing）发表教学案例。2023年获得北大汇丰商学院“教学科研杰出奖”，2019年入选深圳市高层次人才计划。