[Purpose/significance] Community tags generated based on the mining of community topics and users' interests in network social platforms can improve the timeliness and accuracy of the definition of community, and solve the difficulties of user information acquisition and network community selection. [Method/process] Through in-depth analysis of the network community, it was determined that the community features can be represented according to the community topics and users' interests. Firstly, the BTM model of topic extraction was used to train the topic model of network social topics, and the pre-label of network social topics was obtained. Then, based on the different important node indexes of community members' interest tag network, the TOPSIS multi-index comprehensive evaluation method was used to mine the overall interest of members, so as to obtain the interest pre-label of members of the network community. After combining the two results, the community tag was generated and optimized. And this paper took "Douban Group" as an example for demonstration. [Result/conclusion] The community tag generation model based on community topics and members' interests can accurately mine the main interests and recent concerns. Tag generation of the community as a whole is conducive to the selection of interest groups of network users.
Jiang Wuxuan
,
Yi Ming
,
Xiong Huixiang
,
Tong Zhaoli
. Research on the Generation of Community Tags in Network Social Platform[J]. Library and Information Service, 2021
, 65(10)
: 79
-89
.
DOI: 10.13266/j.issn.0252-3116.2021.10.009
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