J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2015 , Vol. 20 >Issue 1: 1 - 6

DOI: https://doi.org/10.1007/s12204-015-1579-x

Sentiment Analysis for Chinese Text Based on Emotion Degree Lexicon and Cognitive Theories

Expand
  • (School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China)

Online published: 2015-03-10

Fold

Abstract

The mass data of social media and social networks generated by users play an important role in tracking users'sentiments and opinions online. A good polarity lexicon which can effectively improve the classification results of sentiment analysis is indispensable to analyze the user’s sentiments. Inspired by social cognitive theories, we combine basic emotion value lexicon and social evidence lexicon to improve traditional polarity lexicon. The proposed method obtains significant improvement in Chinese text sentiment analysis by using the proposed lexicon and new syntactic analysis method.

Key words： Chinese text; sentiment analysis; emotion lexicon; social cognitive theory; emotion tendency

Cite this article

WU Xing* (武 星), Lü Hai-tao (吕海涛), ZHUO Shao-jian (卓少剑) . Sentiment Analysis for Chinese Text Based on Emotion Degree Lexicon and Cognitive Theories[J]. Journal of Shanghai Jiaotong University(Science), 2015 , 20(1) : 1 -6 . DOI: 10.1007/s12204-015-1579-x

References

[1] Eirinaki M, Pisal S, Singh J. Feature-based opinion mining and ranking [J]. Journal of Computer and System Sciences, 2012, 78(4): 1175-1184.
[2] Zhai Z W, Liu B, Xu H, et al. Clustering product features for opinion mining [C]//Proceedings of the Fourth ACM International Conference on Web Search and Data Mining. New York, USA: ACM, 2011: 347-354.
[3] Liu B. Sentiment analysis and opinion mining: Synthesis lectures on human language technologies [M]. [s.l.]: Morgan & Claypool Publishers, 2012: 1-167.
[4] Maas A L, Daly R E, Pham P T, et al. Learning word vectors for sentiment analysis [C]//Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies.[s. l.]: Association for Computational Linguistics,2011: 142-150.
[5] Liu B. Sentiment analysis and subjectivity [C]//Handbook of Natural Language Processing.New York: CRC Press, 2010: 627-666.
[6] Liu B, Zhang L. A survey of opinion mining and sentiment analysis [C]//Mining Text Data. Berlin, Germany:Springer-Verlag, 2012: 415-463.
[7] Kouloumpis E, Wilson T, Moore J. Twitter sentiment analysis: The good the bad and the omg![C]//Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. Barcelona,Spain: AAAI, 2011: 538-541.
[8] Pak A, Paroubek P. Twitter as a corpus for sentiment analysis and opinion mining [C]// Seventh International Conference on Language Resources and Evaluation.Valletta, Malta: LREC, 2010: 1320-1326.
[9] Cambria E, Hussain A, Durrani T, et al. Towards a Chinese common and common sense knowledge base for sentiment analysis [C]//Advanced Research in Applied Artificial Intelligence. Berlin, Germany:Springer-Verlag, 2012: 437-446.
[10] Miao Y Q, Su J, Liu S B, et al. SOCAL based method for Chinese sentiment analysis[C]//Informatics and Management Science IV. Berlin,Germany: Springer-Verlag, 2013: 345-351.
[11] Yang L, Lin H F, Lin Y. Sentiment analysis based on chinese thinking modes [C]//Natural Language Processing and Chinese Computing. Berlin, Germany:Springer-Verlag, 2012: 46-57.
[12] Rochat P. Early social cognition: Understanding others in the first months of life [M]. London, UK: Psychology Press, 2014.
[13] Thompson J D. Organizations in action: Social science bases of administrative theory [M]. Livingston,USA: Transaction Publishers, 2011.
[14] Thompson J B.Media and modernity: A social theory of the media [M]. Hoboken, US: John Wiley & Sons,2013.
[15] Qian Y, Adali S. Extended structural balance theory for modeling trust in social networks [C]//2013 Eleventh Annual International Conference on Privacy,Security and Trust (PST). Tarragonna, Spain: IEEE,2013: 283-290.
[16] Tawari A, Trivedi M M. Speech emotion analysis:Exploring the role of context [J]. IEEE Transactions on Multimedia, 2010, 12(6): 502-509.
[17] Balahur A, Steinberger R, Kabadjov M, et al.Sentiment analysis in the news [C]// Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC’2010). Valletta, Malta: [s. n.],2010: 2216-2220.
[18] Johnston P H. Opening minds: Using language to change lives [M]. Portland: Stenhouse Publishers,2012.
[19] Beattie G, Ellis A. The psychology of language and communication [M]. London, UK: Psychology Press,2014.
[20] Thelwall M, Buckley K. Topic-based sentiment analysis for the social Web: The role of mood and issue-related words [J]. Journal of the American Society for Information Science and Technology, 2013,64(8): 1608-1617.
[21] Guerra P C, Meira Jr W, Cardie C. Sentiment analysis on evolving social streams: how self-report imbalances can help [C]//Proceedings of the 7th ACM International Conference on Web Search and Data Mining.Helsinki, Finland: ACM, 2014: 443-452.
[22] Tsai A C R, Wu C E, Tsai R T H, et al. Building a concept-level sentiment dictionary based on commonsense knowledge [J]. IEEE Intelligent Systems, 2013,28(2): 22-30.
Options
Outlines

/

〈 〉