[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.
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