Studying Content Interaction Data with Topic Model and Sentiment Analysis
Xu Hongxia,Yu Qianqian(),Qian Li
National Science Library, Chinese Academy of Sciences, Beijing 100190, China;Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
[Objective] This paper explores data mining techniques for confrontational opinions from interaction data of online community.[Methods] First, we constructed a new algorithm to analyze emotional confrontations based on sentiment analysis and topic model. Then, we included the characteristics of knowledge, topic, and interaction data to the new model. Finally, we conducted an empirical study on the topic of AlphaGo.[Results] There was significant “Pro-AlphaGo” and “Anti-AlphaGo” confrontations online. The “Pro-AlphaGo” topics included human intelligence, competition and ability. The “Anti-AlphaGo” opinions covered AI companies, products and comprehension abilities.[Limitations] We only examined the proposed model with the topic of AlphaGo.[Conclusions] The proposed method benefits intelligence analysis.
徐红霞,于倩倩,钱力. 基于主题模型和情感分析的话题交互数据观点对抗性分析 *[J]. 数据分析与知识发现, 2020, 4(7): 110-117.
Xu Hongxia,Yu Qianqian,Qian Li. Studying Content Interaction Data with Topic Model and Sentiment Analysis. Data Analysis and Knowledge Discovery, 2020, 4(7): 110-117.
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