%A Li Zhen,Ding Shengchun,Wang Nan %T Identifying Topics of Online Public Opinion %0 Journal Article %D 2017 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2017.08.03 %P 18-30 %V 1 %N 8 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4409.shtml} %8 2017-08-25 %X

[Objective] This paper aims to identify the topics of online public opinion. [Methods] We constructed a model to extract public opinion based on the information content of the Weibo posts, the relationship among the users, and user behaviors. [Results] We built a public opinion network, extracted and clustered relevant topics, constructed a two-mode network of “user-topic” and evolution of the opinion topics. The proposed method could identify topics of online public opinion effectively. [Limitations] The influence of users’ attributes on topic identification needed to be investigated. [Conclusions] We could identify the topics of online public opinion based on the social network analysis with the help of LDA model.