Affective computing and game theory based prediction for online reviews

被引：0

作者：

Bu, Zhan ^{[1
]}

Wu, Zhi-Ang ^{[1
]}

Cao, Jie ^{[1
]}

Zhu, Gui-Xiang ^{[2
]}

机构：

[1] Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics, Nanjing, 210003, Jiangsu

[2] College of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2015年 / 43卷 / 12期

关键词：

Affective computing; Emotional evolution; Game theory; Online reviews; Sentiment analysis;

D O I：

10.3969/j.issn.0372-2112.2015.12.028

中图分类号：

学科分类号：

摘要：

Most of the existing sentiment analysis was performed in the sentiment classification for subjective texts; the emotional evolution analysis for complex interactive texts was not yet thoroughly targeted by the research community. This paper is concerned on short-text Chinese online reviews collected from Tianya forum. Firstly, an efficient affective computing framework is proposed to capture the underlying emotions of online reviews. Secondly, a game theory based emotional evolution prediction algorithm combining the affective computing is proposed, in which the mixed Nash Equilibrium strategies are calculated as the future emotional behavior of interactive users. Experimental results on the large-scaled review dataset are provided to demonstrate the effectiveness and accurateness of our approaches. © 2015, Chinese Institute of Electronics. All right reserved.

引用

页码：2530 / 2535

页数：5

共 11 条

[1]

Zhao Y.Y., Qin B., Liu T., Sentiment analysis, Journal of Software, 21, 8, pp. 1834-1848, (2010)

[2]

Hatzivassiloglou V., McKeown K.R., Predicting the semantic orientation of adjectives, Proceedings of the 35th ACL, pp. 174-181, (1997)

[3]

Turney P.D., Littman M.L., Measuring praise and criticism: Inference of semantic orientation from association, ACM Transactions on Information Systems, 21, 4, pp. 315-346, (2003)

[4]

Hu M., Liu B., Mining and summarizing customer reviews, Proceedings of the 10th KDD, pp. 168-177, (2004)

[5]

Pang B., Lillian L., Shivakumar V., Thumbs up?: sentiment classification using machine learning techniques, Proceedings of the EMNLP, pp. 79-86, (2002)

[6]

Galik M., Rank S., Modelling emotional trajectories of individuals in an online chat, Proceedings of the 10th MATES, pp. 96-105, (2012)

[7]

Li T.M.H., Chau M., Wong P.W.C., Et al., A hybrid system for online detection of emotional distress, Proceedings of PAISI 2012, pp. 73-80, (2012)

[8]

Myerson R.B., Game Theory: Analysis of Conflict, (2013)

[9]

Haythornthwaite C., Social network analysis: An approach and technique for the study of information exchange, Library & Information Science Research, 18, 4, pp. 323-342, (1996)

[10]

Yee N., The psychology of massively multi-user online role-playing games: Motivations, emotional investment, relationships and problematic usage, Avatars at Work and Play, 34, pp. 187-207, (2006)

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