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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 |
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Abstract [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.
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Received: 03 December 2018
Published: 25 July 2020
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Corresponding Authors:
Yu Qianqian
E-mail: yuqianqian@mail.las.ac.cn
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