Current State of Text Sentiment Analysis from Opinion to Emotion Mining

Abstract

Sentiment analysis from text consists of extracting information about opinions, sentiments, and even emotions conveyed by writers towards topics of interest. It is often equated to opinion mining, but it should also encompass emotion mining. Opinion mining involves the use of natural language processing and machine learning to determine the attitude of a writer towards a subject. Emotion mining is also using similar technologies but is concerned with detecting and classifying writers emotions toward events or topics. Textual emotion-mining methods have various applications, including gaining information about customer satisfaction, helping in selecting teaching materials in e-learning, recommending products based on users emotions, and even predicting mental-health disorders. In surveys on sentiment analysis, which are often old or incomplete, the strong link between opinion mining and emotion mining is understated. This motivates the need for a different and new perspective on the literature on sentiment analysis, with a focus on emotion mining. We present the state-of-the-art methods and propose the following contributions: (1) a taxonomy of sentiment analysis; (2) a survey on polarity classification methods and resources, especially those related to emotion mining; (3) a complete survey on emotion theories and emotion-mining research; and (4) some useful resources, including lexicons and datasets.

References

1. Cecilia Ovesdotter Alm, Dan Roth, and Richard Sproat. 2005. Emotions from text: Machine learning for text-based emotion prediction. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 579--586.
2. Cecilia Ovesdotter Alm and Richard Sproat. 2005. Emotional sequencing and development in fairy tales. In Affective Computing and Intelligent Interaction. Springer, 668--674.
3. Ebba Cecilia Ovesdotter Alm. 2008. Affect in Text and Speech. ProQuest.
4. Alina Andreevskaia and Sabine Bergler. 2006. Mining wordnet for a fuzzy sentiment: Sentiment tag extraction from wordnet glosses. In EACL, Vol. 6. 209--215.
5. Anthony Aue and Michael Gamon. 2005. Customizing sentiment classifiers to new domains: A case study. In Proceedings of Recent Advances in Natural Language Processing (RANLP), Vol. 1. Citeseer.
6. Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In LREC, Vol. 10. 2200--2204.
7. Collin F. Baker, Charles J. Fillmore, and John B. Lowe. 1998. The berkeley framenet project. In Proceedings of the 17th International Conference on Computational Linguistics-Volume 1. Association for Computational Linguistics, 86--90.
8. Farah Benamara, Carmine Cesarano, Antonio Picariello, Diego Reforgiato Recupero, and Venkatramana S. Subrahmanian. 2007. Sentiment analysis: Adjectives and adverbs are better than adjectives alone. In ICWSM.
9. Plaban Kumar Bhowmick. 2009. Reader perspective emotion analysis in text through ensemble based multi-label classification framework. Comput. Inf. Sci. 2, 4 (2009), 64--74.
10. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. J. Mach. Learn. Res. 3 (2003), 993--1022.
11. John Blitzer, Mark Dredze, and Fernando Pereira. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In ACL, Vol. 7. Citeseer, 440--447.
12. Johan Bollen, Huina Mao, and Alberto Pepe. 2011. Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. In ICWSM.
13. Carlos Busso, Zhigang Deng, Serdar Yildirim, Murtaza Bulut, Chul Min Lee, Abe Kazemzadeh, Sungbok Lee, Ulrich Neumann, and Shrikanth Narayanan. 2004. Analysis of emotion recognition using facial expressions, speech and multimodal information. In Proceedings of the 6th International Conference on Multimodal Interfaces. ACM, 205--211.
14. François-Régis Chaumartin. 2007. UPAR7: A knowledge-based system for headline sentiment tagging. In Proceedings of the 4th International Workshop on Semantic Evaluations. Association for Computational Linguistics, 422--425.
15. P. E. Corcoran. 2006. Emotional framing in australian journalism. In Australian 8 New Zealand Communication Association International Conference, Adelaide, Australia (ANZCA).
16. Taner Danisman and Adil Alpkocak. 2008. Feeler: Emotion classification of text using vector space model. In AISB 2008 Convention Communication, Interaction and Social Intelligence, Vol. 1. 53.
17. Amitava Das and Sivaji Bandyopadhyay. 2010. SentiWordNet for indian languages. Asian Federation for Natural Language Processing, China (2010), 56--63.
18. Sanjiv Das and Mike Chen. 2001. Yahoo! for amazon: Extracting market sentiment from stock message boards. In Proceedings of the Asia Pacific Finance Association Annual Conference (APFA), Vol. 35. Bangkok, Thailand, 43.
19. Kushal Dave, Steve Lawrence, and David M. Pennock. 2003. Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In Proceedings of the 12th International Conference on World Wide Web. ACM, 519--528.
20. Munmun De Choudhury, Michael Gamon, Scott Counts, and Eric Horvitz. 2013. Predicting depression via social media. In ICWSM.
21. Kerstin Denecke and Yihan Deng. 2015. Sentiment analysis in medical settings: New opportunities and challenges. Artif. Intell. Med. 64, 1 (2015), 17--27.
22. Sidney K. D’mello and Jacqueline Kory. 2015. A review and meta-analysis of multimodal affect detection systems. ACM Comput. Surv. 47, 3 (2015), 43.
23. Cícero Nogueira dos Santos and Maira Gatti. 2014. Deep convolutional neural networks for sentiment analysis of short texts. In COLING. 69--78.
24. Paul Ekman. 1992. An argument for basic emotions. Cogn. Emot. 6, 3--4 (1992), 169--200.
25. Paul Ekman, Wallace V. Friesen, and Phoebe Ellsworth. 1972. Emotion in the human face: Guidelines for research and an integration of findings. New York. Permagon.
26. Moataz El Ayadi, Mohamed S. Kamel, and Fakhri Karray. 2011. Survey on speech emotion recognition: Features, classification schemes, and databases. Pattern Recogn. 44, 3 (2011), 572--587.
27. Andrea Esuli and Fabrizio Sebastiani. 2005. Determining the semantic orientation of terms through gloss classification. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management. ACM, 617--624.
28. Andrea Esuli and Fabrizio Sebastiani. 2006a. Determining term subjectivity and term orientation for opinion mining. In EACL, Vol. 6. 2006.
29. Andrea Esuli and Fabrizio Sebastiani. 2006b. Sentiwordnet: A publicly available lexical resource for opinion mining. In Proceedings of LREC, Vol. 6. 417--422.
30. Aidan Finn and Nicholas Kushmerick. 2006. Learning to classify documents according to genre. J. Am. Soc. Inf. Sci. Technol. 57, 11 (2006), 1506--1518.
31. Elaine Fox. 2008. Emotion Science Cognitive and Neuroscientific Approaches to Understanding Human Emotions. Palgrave Macmillan.
32. Michael Gamon. 2004. Sentiment classification on customer feedback data: Noisy data, large feature vectors, and the role of linguistic analysis. In Proceedings of the 20th International Conference on Computational Linguistics. Association for Computational Linguistics, 841.
33. Michael Gamon and Anthony Aue. 2005. Automatic identification of sentiment vocabulary: Exploiting low association with known sentiment terms. In Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing. Association for Computational Linguistics, 57--64.
34. Bo Gao, Bettina Berendt, and Joaquin Vanschoren. 2015a. Who is more positive in private? Analyzing sentiment differences across privacy levels and demographic factors in facebook chats and posts. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015. ACM, 605--610.
35. Kai Gao, Hua Xu, and Jiushuo Wang. 2015b. Emotion cause detection for chinese micro-blogs based on ECOCC model. In Advances in Knowledge Discovery and Data Mining. Springer, 3--14.
36. Ameneh Gholipour Shahraki. 2015. Emotion Detection from Text. Master’s thesis. University of Alberta.
37. Narendra Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio. 2013. Emotion detection in email customer care. Comput. Intell. 29, 3 (2013), 489--505.
38. Jeffrey T. Hancock, Christopher Landrigan, and Courtney Silver. 2007. Expressing emotion in text-based communication. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 929--932.
39. Maryam Hasan, Emmanuel Agu, and Elke Rundensteiner. 2014. Using hashtags as labels for supervised learning of emotions in Twitter messages. In Proceedings of the Health Informatics Workshop (HI-KDD).
40. Vasileios Hatzivassiloglou and Kathleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of the 8th Conference on European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 174--181.
41. Vasileios Hatzivassiloglou and Janyce M. Wiebe. 2000. Effects of adjective orientation and gradability on sentence subjectivity. In Proceedings of the 18th Conference on Computational Linguistics-Volume 1. Association for Computational Linguistics, 299--305.
42. Dung T. Ho and Tru H. Cao. 2012. A high-order hidden Markov model for emotion detection from textual data. In Knowledge Management and Acquisition for Intelligent Systems. Springer, 94--105.
43. Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 168--177.
44. Xia Hu, Jiliang Tang, Huiji Gao, and Huan Liu. 2013. Unsupervised sentiment analysis with emotional signals. In Proceedings of the 22nd International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, 607--618.
45. Mukesh Jain and V. Kulkarni. 2014. TexEmo: Conveying emotion from text-the study. Int. J. Comput. Appl. 86, 4 (2014), 43--49.
46. Jing Jiang and ChengXiang Zhai. 2007. Instance weighting for domain adaptation in NLP. In ACL, Vol. 7. Citeseer, 264--271.
47. Nitin Jindal and Bing Liu. 2008. Opinion spam and analysis. In Proceedings of the 2008 International Conference on Web Search and Data Mining. ACM, 219--230.
48. Yohan Jo and Alice H. Oh. 2011. Aspect and sentiment unification model for online review analysis. In Proceedings of the 4th ACM International Conference on Web Search and Data Mining. ACM, 815--824.
49. Nobuhiro Kaji and Masaru Kitsuregawa. 2006. Automatic construction of polarity-tagged corpus from HTML documents. In Proceedings of the COLING/ACL on Main Conference Poster Sessions. Association for Computational Linguistics, 452--459.
50. Nobuhiro Kaji and Masaru Kitsuregawa. 2007. Building lexicon for sentiment analysis from massive collection of HTML documents.. In EMNLP-CoNLL. Citeseer, 1075--1083.
51. Jaap Kamps, M. J. Marx, Robert J. Mokken, and Maarten De Rijke. 2004. Using wordnet to measure semantic orientations of adjectives. Language Resources and Evaluation Conference (LREC) 4 (2004), 1115--1118.
52. Daekook Kang and Yongtae Park. 2014. Review-based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach. Expert Syst. Appl. 41, 4 (2014), 1041--1050.
53. E. C.-C. Kao, Chun-Chieh Liu, Ting-Hao Yang, Chang-Tai Hsieh, and Von-Wun Soo. 2009. Towards text-based emotion detection a survey and possible improvements. In Proceedings of the 2009 International Conference on Information Management and Engineering (ICIME’09). IEEE, 70--74.
54. Phil Katz, Matthew Singleton, and Richard Wicentowski. 2007. Swat-mp: The semeval-2007 systems for task 5 and task 14. In Proceedings of the 4th International Workshop on Semantic Evaluations. Association for Computational Linguistics, 308--313.
55. Sunghwan Mac Kim, Alessandro Valitutti, and Rafael A Calvo. 2010. Evaluation of unsupervised emotion models to textual affect recognition. In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. Association for Computational Linguistics, 62--70.
56. Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, and Saif Mohammad. 2014. NRC-Canada-2014: Detecting aspects and sentiment in customer reviews. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Association for Computational Linguistics and Dublin City University, Dublin, Ireland, 437--442.
57. Andrea Kleinsmith and Nadia Bianchi-Berthouze. 2013. Affective body expression perception and recognition: A survey. IEEE Trans. Affect. Comput. 4, 1 (2013), 15--33.
58. Sophia Yat Mei Lee, Ying Chen, Shoushan Li, and Chu-Ren Huang. 2010. Emotion cause events: Corpus construction and analysis. In LREC.
59. Jingsheng Lei, Yanghui Rao, Qing Li, Xiaojun Quan, and Liu Wenyin. 2014. Towards building a social emotion detection system for online news. Fut. Gen. Comput. Syst. 37 (2014), 438--448.
60. Shoushan Li, Yunxia Xue, Zhongqing Wang, and Guodong Zhou. 2013. Active learning for cross-domain sentiment classification. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence. AAAI Press, 2127--2133.
61. Tao Li, Vikas Sindhwani, Chris Ding, and Yi Zhang. 2009. Knowledge transformation for cross-domain sentiment classification. In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 716--717.
62. Weiyuan Li and Hua Xu. 2014. Text-based emotion classification using emotion cause extraction. Expert Syst. Appl. 41, 4 (2014), 1742--1749.
63. Chenghua Lin and Yulan He. 2009. Joint sentiment/topic model for sentiment analysis. In Proceedings of the 18th ACM Conference on Information and Knowledge Management. ACM, 375--384.
64. Wei-Hao Lin, Theresa Wilson, Janyce Wiebe, and Alexander Hauptmann. 2006. Which side are you on?: Identifying perspectives at the document and sentence levels. In Proceedings of the 10th Conference on Computational Natural Language Learning. Association for Computational Linguistics, 109--116.
65. Bing Liu. 2011. Opinion mining and sentiment analysis. In Web Data Mining. Springer, 459--526.
66. Bing Liu. 2012. Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5, 1 (2012), 1--167.
67. Bing Liu. 2015. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions. Cambridge University Press.
68. Bing Liu, Minqing Hu, and Junsheng Cheng. 2005. Opinion observer: Analyzing and comparing opinions on the web. In Proceedings of the 14th International Conference on World Wide Web. ACM, 342--351.
69. Hugo Lövheim. 2012. A new three-dimensional model for emotions and monoamine neurotransmitters. Med. Hypoth. 78, 2 (2012), 341--348.
70. Kim Luyckx, Frederik Vaassen, Claudia Peersman, and Walter Daelemans. 2012. Fine-grained emotion detection in suicide notes: A thresholding approach to multi-label classification. Biomed. Inf. Insights 5, Suppl. 1 (2012), 61.
71. D. A. Medler, A. Arnoldussen, J. R. Binder, and M. S. Seidenberg. 2005. The Wisconsin Perceptual Attribute Ratings Database. Retrieved from http://www.neuro.mcw.edu/ratings/.
72. Prem Melville, Wojciech Gryc, and Richard D. Lawrence. 2009. Sentiment analysis of blogs by combining lexical knowledge with text classification. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 1275--1284.
73. Gilad Mishne. 2005. Experiments with mood classification in blog posts. In Proceedings of ACM SIGIR 2005 Workshop on Stylistic Analysis of Text for Information Access, Vol. 19. Citeseer.
74. Gilad Mishne and Maarten De Rijke. 2006. Capturing global mood levels using blog posts. In AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs. 145--152.
75. Saif M. Mohammad and Peter D. Turney. 2010. Emotions evoked by common words and phrases: Using mechanical turk to create an emotion lexicon. In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. Association for Computational Linguistics, 26--34.
76. Saif M. Mohammad. 2012. # Emotional tweets. In Proceedings of the 1st Joint Conference on Lexical and Computational Semantics-Volume 1: Proceedings of the Main Conference and the Shared Task, and Volume 2: Proceedings of the 6th International Workshop on Semantic Evaluation. Association for Computational Linguistics, 246--255.
77. Saif M. Mohammad, Svetlana Kiritchenko, and Xiaodan Zhu. 2013. NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets. In Proceedings of the 7th International Workshop on Semantic Evaluation Exercises (SemEval’13).
78. Louis-Philippe Morency, Rada Mihalcea, and Payal Doshi. 2011. Towards multimodal sentiment analysis: Harvesting opinions from the web. In Proceedings of the 13th International Conference on Multimodal Interfaces. ACM, 169--176.
79. Arjun Mukherjee and Bing Liu. 2012. Aspect extraction through semi-supervised modeling. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1. Association for Computational Linguistics, 339--348.
80. Tony Mullen and Nigel Collier. 2004. Sentiment analysis using support vector machines with diverse information sources. In EMNLP, Vol. 4. 412--418.
81. Sean M. Murphy, Bernard Maskit, and Wilma Bucci. 2015. Putting feelings into words: Cross-linguistic markers of the referential process. NAACL HLT 2015 (2015), 80.
82. Jin-Cheon Na, Haiyang Sui, Christopher Khoo, Syin Chan, and Yunyun Zhou. 2004. Effectiveness of simple linguistic processing in automatic sentiment classification of product reviews. Adv. Knowl. Org. 9 (2004), 49--54.
83. Tetsuya Nasukawa and Jeonghee Yi. 2003. Sentiment analysis: Capturing favorability using natural language processing. In Proceedings of the 2nd International Conference on Knowledge Capture. ACM, 70--77.
84. Alena Neviarouskaya, Helmut Prendinger, and Mitsuru Ishizuka. 2007. Textual affect sensing for sociable and expressive online communication. In Affective Computing and Intelligent Interaction. Springer, 218--229.
85. Alena Neviarouskaya, Helmut Prendinger, and Mitsuru Ishizuka. 2009. Compositionality principle in recognition of fine-grained emotions from text. In ICWSM.
86. Vincent Ng, Sajib Dasgupta, and S. M. Arifin. 2006. Examining the role of linguistic knowledge sources in the automatic identification and classification of reviews. In Proceedings of the COLING/ACL on Main Conference Poster Sessions. Association for Computational Linguistics, 611--618.
87. Alvaro Ortigosa, José M. Martín, and Rosa M. Carro. 2014. Sentiment analysis in facebook and its application to e-learning. Comput. Hum. Behav. 31 (2014), 527--541.
88. Sinno Jialin Pan, Xiaochuan Ni, Jian-Tao Sun, Qiang Yang, and Zheng Chen. 2010. Cross-domain sentiment classification via spectral feature alignment. In Proceedings of the 19th International Conference on World Wide Web. ACM, 751--760.
89. Bo Pang and Lillian Lee. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics. Association for Computational Linguistics, 271.
90. Bo Pang and Lillian Lee. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics. Association for Computational Linguistics, 115--124.
91. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Found. Trends Inf. Retriev. 2, 1--2 (2008), 1--135.
92. Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan. 2002. Thumbs up?: Sentiment classification using machine learning techniques. In Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing-Volume 10. Association for Computational Linguistics, 79--86.
93. James W. Pennebaker. 1997. Writing about emotional experiences as a therapeutic process. Psychol. Sci. 8, 3 (1997), 162--166.
94. James W. Pennebaker, R. J. Booth, and M. E. Francis. 2007. Linguistic inquiry and word count: LIWC. Austin, TX: liwc. net (2007).
95. Robert Plutchik and Henry Kellerman. 1986. Emotion: Theory, Research and Experience. Vol. 3. Academic Press, New York, NY.
96. Rudy Prabowo and Mike Thelwall. 2009. Sentiment analysis: A combined approach. J. Inform. 3, 2 (2009), 143--157.
97. Likun Qiu, Weishi Zhang, Changjian Hu, and Kai Zhao. 2009. Selc: A self-supervised model for sentiment classification. In Proceedings of the 18th ACM Conference on Information and Knowledge Management. ACM, 929--936.
98. Francisco Rangel and Paolo Rosso. 2016. On the impact of emotions on author profiling. Information Processing 8 Management 52, 1 (2016), 73--92.
99. Yanghui Rao, Qing Li, Liu Wenyin, Qingyuan Wu, and Xiaojun Quan. 2014. Affective topic model for social emotion detection. Neur. Netw. 58 (2014), 29--37.
100. Kirk Roberts, Michael A. Roach, Joseph Johnson, Josh Guthrie, and Sanda M. Harabagiu. 2012. EmpaTweet: Annotating and detecting emotions on Twitter. In LREC. 3806--3813.
101. James A. Russell, José-Miguel Fernández-Dols, Anthony S. R. Manstead, and Jane C. Wellenkamp. 2013. Everyday Conceptions of Emotion: An Introduction to the Psychology, Anthropology and Linguistics of Emotion. Vol. 81. Springer Science 8 Business Media.
102. Robert E. Schapire. 1999. A brief introduction to boosting. In Ijcai, Vol. 99. 1401--1406.
103. Klaus R. Scherer and Harald G. Wallbott. 1994. Evidence for universality and cultural variation of differential emotion response patterning. J. Pers. Soc. Psychol. 66, 2 (1994), 310.
104. Fabrizio Sebastiani. 2002. Machine learning in automated text categorization. ACM Comput. Surv. 34, 1 (2002), 1--47.
105. Phillip Shaver, Judith Schwartz, Donald Kirson, and Cary O’connor. 1987. Emotion knowledge: Further exploration of a prototype approach. J. Pers. Soc. Psychol. 52, 6 (1987), 1061.
106. Richard Socher, Alex Perelygin, Jean Y. Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Vol. 1631. Citeseer, 1642.
107. Philip Stone, Dexter C. Dunphy, Marshall S. Smith, and D. M. Ogilvie. 1968. The general inquirer: A computer approach to content analysis. J. Region. Sci. 8, 1 (1968), 113--116.
108. Carlo Strapparava and Rada Mihalcea. 2007. Semeval-2007 task 14: Affective text. In Proceedings of the 4th International Workshop on Semantic Evaluations. Association for Computational Linguistics, 70--74.
109. Carlo Strapparava and Rada Mihalcea. 2008. Learning to identify emotions in text. In Proceedings of the 2008 ACM Symposium on Applied Computing. ACM, 1556--1560.
110. Carlo Strapparava and Alessandro Valitutti. 2004. WordNet affect: An affective extension of wordnet. In LREC, Vol. 4. 1083--1086.
111. Hiroya Takamura, Takashi Inui, and Manabu Okumura. 2007. Extracting semantic orientations of phrases from dictionary. In HLT-NAACL, Vol. 2007. 292--299.
112. Songbo Tan, Gaowei Wu, Huifeng Tang, and Xueqi Cheng. 2007. A novel scheme for domain-transfer problem in the context of sentiment analysis. In Proceedings of the 16th ACM Conference on Conference on Information and Knowledge Management. ACM, 979--982.
113. Duyu Tang. 2015. Sentiment-specific representation learning for document-level sentiment analysis. In Proceedings of the 8th ACM International Conference on Web Search and Data Mining. ACM, 447--452.
114. Duyu Tang, Furu Wei, Bing Qin, Ting Liu, and Ming Zhou. 2014a. Coooolll: A deep learning system for Twitter sentiment classification. In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). 208--212.
115. Duyu Tang, Furu Wei, Nan Yang, Ming Zhou, Ting Liu, and Bing Qin. 2014b. Learning sentiment-specific word embedding for Twitter sentiment classification. In ACL (1). 1555--1565.
116. Peter D. Turney. 2002. Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Association for Computational Linguistics, 417--424.
117. S. Voeffray. 2011. Emotion-sensitive human-computer interaction (HCI): State of the art-Seminar paper. Emotion Recognition. p1-4 (2011).
118. Xuan-Son Vu and Seong-Bae Park. 2014. Construction of vietnamese SentiWordNet by using vietnamese dictionary. In Proceedings of the 40th Conference of the Korea Information Processing Society. 745--748.
119. Joseph B. Walther. 1992. Interpersonal effects in computer-mediated interaction a relational perspective. Commun. Res. 19, 1 (1992), 52--90.
120. Joseph B. Walther, Tracy Loh, and Laura Granka. 2005. Let me count the ways the interchange of verbal and nonverbal cues in computer-mediated and face-to-face affinity. J. Lang. Soc. Psychol. 24, 1 (2005), 36--65.
121. Shuai Wang, Zhiyuan Chen, and Bing Liu. 2016. Mining aspect-specific opinion using a holistic lifelong topic model. In Proceedings of the 25th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, 167--176.
122. Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, and Amit P. Sheth. 2012. Harnessing Twitter “big data” for automatic emotion identification. In Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom). IEEE, 587--592.
123. Casey Whitelaw, Navendu Garg, and Shlomo Argamon. 2005. Using appraisal groups for sentiment analysis. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management. ACM, 625--631.
124. Janyce Wiebe, Theresa Wilson, Rebecca Bruce, Matthew Bell, and Melanie Martin. 2004. Learning subjective language. Comput. Ling. 30, 3 (2004), 277--308.
125. Alicja Wieczorkowska, Piotr Synak, and Zbigniew W. Raś. 2006. Multi-label classification of emotions in music. In Intelligent Information Processing and Web Mining. Springer, 307--315.
126. Theresa Wilson, Paul Hoffmann, Swapna Somasundaran, Jason Kessler, Janyce Wiebe, Yejin Choi, Claire Cardie, Ellen Riloff, and Siddharth Patwardhan. 2005a. OpinionFinder: A system for subjectivity analysis. In Proceedings of hlt/emnlp on Interactive Demonstrations. Association for Computational Linguistics, 34--35.
127. Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2005b. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 347--354.
128. Hui Yang, Jamie Callan, and Luo Si. 2006. Knowledge transfer and opinion detection in the TREC 2006 blog track. In TREC.
129. Yi-Hsuan Yang and Homer H. Chen. 2012. Machine recognition of music emotion: A review. ACM Trans. Intell. Syst. Technol. 3, 3 (2012), 40.
130. Hong Yu and Vasileios Hatzivassiloglou. 2003. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 129--136.
131. Zhihong Zeng, Maja Pantic, Glenn I. Roisman, and Thomas S. Huang. 2009. A survey of affect recognition methods: Audio, visual, and spontaneous expressions. IEEE Trans. Pattern Anal. Mach. Intell. 31, 1 (2009), 39--58.
132. Yaowen Zhang, Lin Shang, and Xiuyi Jia. 2015. Sentiment analysis on microblogging by integrating text and image features. In Advances in Knowledge Discovery and Data Mining. Springer, 52--63.
133. Xiaodan Zhu, Svetlana Kiritchenko, and Saif M. Mohammad. 2014. NRC-canada-2014: Recent improvements in the sentiment analysis of tweets. SemEval 2014 (2014), 443.
134. Xiaodan Zhu, Svetlana Kiritchenko, and Saif M. Mohammad. 2014. Sentiment analysis of short informal texts. J. Artif. Intell. Res. 50 (2014), 723--762.

Index Terms

• General and reference

  • Document types

    • Surveys and overviews

• Information systems

  • Information systems applications

    • Data mining