在线社区用户画像及自我呈现主题挖掘——以网易云音乐社区为例

Mining Online User Profiles and Self-Presentations: Case Study of NetEase Music Community

【目的】以网易云音乐社区为研究对象,分析在线社区中用户自我呈现的内容特征、演化规律、群体差异及自我呈现对社区认可的影响等问题。【方法】从资历和参与度两个维度构建用户画像,通过BERT方法进行短文本评论聚类,挖掘自我呈现的内容主题,利用余弦相似度等方法分析用户自我呈现内容主题的演化规律和群体差异,采用协方差分析用户自我呈现内容主题对社区认可度的影响。【结果】用户自我呈现的内容主题分为8类;“听后感”主题占比逐年降低,“回忆往事”等主题呈上升趋势;“寻求互动”等主题在“放松”等曲风下占比要高于其他曲风;除“寻求互动”主题外,各主题在不同时间点上占比一致;“回忆往事”等主题下高资历用户的余弦相似度高于低资历用户;持续参与用户的余弦相似度高于边缘参与者;用户自我呈现内容主题对其社区认可度的影响在10%的置信度水平下显著。【局限】未针对其他类型的在线社区进行更深入的研究。【结论】用户自我呈现的内容主题以“回忆往事”为主,会受到曲风等因素的影响,内容主题随社区发展呈现泛化趋势且不同用户群体之间有明显差异,在线社区中用户对自我呈现内容主题有一定的偏好。

[Objective] This paper explores patterns, evolutionary laws, group differences and influences on community recognition of online users’ self-presentation topics. [Methods] Firstly, we identified online users of NetEase music community and constructed their profiles from the perspectives of qualification and participation.Then, we adopted the BERT model to cluster users’ short comments, and identified their self-presentation topics.Third, we utilized cosine similarity to analyze the evolution of topics and group differences. Finally, we used covariance to analyze the impacts of self-presentation topics on community recognition. [Results] There are eight self-presentation topics, while the proportion of“reviews”decreased and“recollection”increased.“Interaction”topics were more popular in“relax”style than in others. The proportion of each topic at different time was almost the same. Under the themes of“recollection”, the cosine similarity value of quality users was higher than those of other users. The cosine similarity of continuous participants was higher than those of the inactive participants. The impact of users’ self-presentation topics on their community recognition was significant at the 0.1 level.[Limitations] More research is needed to examine users of other online communities. [Conclusions]“Recollection”is the most popular one among users’ self-presentation topics, which are affected by styles and time. There was a diversity trend for the topics with the development of the community, as well as obvious differences among user groups.