1School of Information Management, Central China Normal University, Wuhan 430079, China 2School of Information Management, Wuhan University, Wuhan 430079, China
[Objective] This paper proposes a method to generate dynamic labels for the characteristics of online communities and their short-term interest. [Methods] Firstly, we used the BTM model to extract the discussion topics from short texts posted by online community members. Then, we explored their actual interest based on personal labels. Finally, we combined these results to create dynamic tags for the communities. [Results] We examined the proposed model empirically with data from two types of “Douban groups”. Tags of discussion topics and characteristics of the communities showed strong and stable relevant relationship. The tags for personal interest could accurately represent the community’s dynamic interest. [Limitations] More online communities should be included in future studies. [Conclusions] The proposed model accurately identifies characteristics of online community and its members’ short-term concerns, which also benefits information acquisition.
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