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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (7): 110-117    DOI: 10.11925/infotech.2096-3467.2018.1362
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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.
Key words： Opinion Mining      Sentiment Analysis      Confrontation Analysis     
Received: 03 December 2018      Published: 25 July 2020
ZTFLH:  TP391  
Corresponding Authors: Yu Qianqian     E-mail: yuqianqian@mail.las.ac.cn
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Hongxia Xu
Qianqian Yu
Li Qian

Cite this article:

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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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.1362     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I7/110

Technical Process
Interactive Data Network
数据ID 回答ID 问题ID 作者ID 作者名 点赞数 文本
1 104384323 41191131 3e9800f109ea6110a47c1a62aa9a7544 bai-xiao-tian-10-28 20 ……柯洁,18岁三冠,现役世界第一。阿法狗,最强围棋人工智能,4-1战胜李世乭……
2 104753993 41191131 078611a0e7dda6409f09bb8022a0d2f0 Dtcj 23 ……阿法狗打算靠什么下赢柯洁?……传统的对弈机器人是根据“一步棋子带来的所有的可能性”来布局的……
… … … … … … …
300 174316878 60279568 5503adb1d7ff5d58f0a76c80cce0e9c4 liang-yi-cong 756 比柯洁逼出更好的alphago更令人惊喜的是,alphago逼出了更好的柯洁……
… … … … … … …
4758 90009325 41171543 51fbc88fa0fa89f561c02d168f936601 liao-feng-95 0 我不认为阿尔法是真正意义上的人工智能。它只是一台按照既定规则做事并且计算能力惊人的电脑……
Zhihu Interactive Data (Partial)
Topic Distribution Visualization on Positive Text
Topic Distribution Visualization on Negative Text
倾向分类 主题一 主题二 主题三
积极倾向 AlphaGo、人类、机器、人工智能、围棋、柯洁、李世石、master、棋手、战胜、算法、学习、期待、科技、强大 人工智能、AlphaGo、人类、战胜、机器、围棋、输、李世石、柯洁、算法、理解、智慧、关注、见证、时代 AlphaGo、人类、围棋、人工智能、李世石、master、战胜、机器、棋手、柯洁、比赛、工具、超越、未来
消极倾向 理解、机器、AlphaGo、人类、围棋、李世石、人工智能、计算、棋手、经验、规则、局限性、打劫、判断、自我意识 输、人类、人工智能、李世石、AlphaGo、机器、战胜、围棋、理解、能力、谷歌、可怕、消灭、未来、统治 理解、AlphaGo、人类、机器、围棋、战胜、李世石、人工智能、算法、直觉、能力、大局观、逻辑、思维、人脑
Adversarial Opinion
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