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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
Li Zhen, Ding Shengchun(), Wang Nan
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
ZTFLH:  TP391 G350  

Cite this article:

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

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微博编号 所属观点
微博编号 所属观点
1 Topic2 115 Topic2
2 Topic1 116 Topic7
3 Topic2 117 Topic6
4 Topic9 118 Topic8
5 Topic6 119 Topic5
6 Topic10 120 Topic4
日期 4月
准确率 0.66 0.53 0.71 0.47 0.6 0.56
观点主题编号 节点入度归一化 观点主题
6 0.19 Topic5
7 0.15 Topic1
8 0.13 Topic9
9 0.13 Topic8
10 0.11 Topic6
11 0.10 Topic2
12 0.06 Topic4
13 0.06 Topic0
14 0.04 Topic3
15 0.03 Topic7
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