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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (8): 18-30    DOI: 10.11925/infotech.2096-3467.2017.08.03
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Identifying Topics of Online Public Opinion
Zhen Li,Shengchun Ding(),Nan Wang
Department of Information Management, Nanjing University of Science and Technology, Nanjing 210094, China
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[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.

Key wordsNetwork Public Opinion      Social Network      LDA Model      Topic Identification      Opinion Topic     
Received: 31 May 2017      Published: 28 September 2017

Cite this article:

Zhen Li,Shengchun Ding,Nan Wang. Identifying Topics of Online Public Opinion. Data Analysis and Knowledge Discovery, 2017, 1(8): 18-30.

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