Mining Online User Profiles and Self-Presentations: Case Study of NetEase Music Community
Wu Jiang1,2,3,Liu Tao3,Liu Yang1,3()
1Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China 2Center for E-commerce Research and Development, Wuhan University, Wuhan 430072, China 3School of Information Management, Wuhan University, Wuhan 430072, China
[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.
吴江, 刘涛, 刘洋. 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*[J]. 数据分析与知识发现, 2022, 6(7): 56-69.
Wu Jiang, Liu Tao, Liu Yang. Mining Online User Profiles and Self-Presentations: Case Study of NetEase Music Community. Data Analysis and Knowledge Discovery, 2022, 6(7): 56-69.
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