Techniques and applications for sentiment analysis: The main applications and challenges of one of the hottest research areas in computer science

Communications of the ACM

Volumn 56, Issue 4, 2013, Pages 82-89

  Feldman, Ronen ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING PROCESS; DOCUMENT ANALYSIS; ENTITY EXTRACTIONS; LINGUISTIC RESOURCES; PART OF SPEECH TAGGING; RELATION EXTRACTION; SENTIMENT ANALYSIS; THOUGHT LEADERS;

COMPUTER SCIENCE; LINGUISTICS;

DATA MINING;

EID: 84875706201     PISSN: 00010782     EISSN: 15577317     Source Type: Journal    
DOI: 10.1145/2436256.2436274     Document Type: Review

References (40)

1. Brooke, J., Tofiloski, M. and Taboada, M. Crosslinguistic sentiment analysis: From English to Spanish. In Proceedings of RANLP (2009).
2. Ding, X., Liu, B. and Yu, P.S. A holistic lexicon-based approach to opinion mining. In Proceedings of the Conference on Web Search and Web Data Mining (2008).
3. Ding, X., Liu, B. and Zhang, L. Entity discovery and assignment for opinion mining applications. In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2009).
4. Dragut, E.C., Yu, C., Sistla, P. and Meng, W. Construction of a sentimental word dictionary. In Proceedings of ACM International Conference on Information and Knowledge Management (2010).
5. Du, W., Tan, S., Cheng, X. and Yun, X. Adapting information bottleneck method for automatic construction of domain-oriented sentiment lexicon. In Proceedings of ACM International Conference on Web Search and Data Mining (2010).
6. Esuli, A. and Sebastiani, F. Determining term subjectivity and term orientation for opinion mining. In Proceedings of Conf. of the European Chapter of the Association for Computational Linguistics (2006).
7. Feldman, R., Rosenfeld, B., Bar-Haim, R. and Fresko, M. The Stock Sonar-Sentiment Analysis of Stocks Based on a Hybrid Approach. IAAI-12 (2011), 1642-1647.
8. Fellbaum, C.D. Wordnet: An Electronic Lexical Database. MIT Press, Cambridge, MA, 1998.
9. Feng, S., Bose, R. and Choi, Y. Learning general connotation of words using graph-based algorithms. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (Edinburgh, Scotland, UK, 2011). 1092-1103.
10. Hai, Z., Chang, K. and Kim, J-J. Implicit feature identification via co-occurrence association rule mining. Computational Linguistics and Intelligent Text Processing (2011), 393-404.
11. Hatzivassiloglou, V. and K. McKeown, Predicting the semantic orientation of adjectives. In Proceedings of the Joint ACL/EACL Conference (1997), 174-181.
12. Hu, M. and Liu, B. Mining and summarizing customer reviews. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2004), 168-177.
13. Hu, M. and Liu, B. Mining opinion features in customer reviews. In Proceedings of AAAI (2004), 755-760.
14. Jakob, N. and Gurevych, I. Extracting opinion targets in a single-and cross-domain setting with conditional random fields. In Proceedings of Conference on Empirical Methods in Natural Language Processing (2010).
15. Jindal, N. and Liu, B. Identifying comparative sentences in text documents. In Proceedings of ACM SIGIR Conf. on Research and Development in Information Retrieval (2006).
16. Kamps, J., Marx, M., Mokken, R.J. and de Rijke, M. Using Word Net to measure semantic orientation of adjectives. LREC, 2004.
17. Kim, S.-M. and Hovy, E. Crystal: Analyzing predictive opinions on the Web. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (2007).
18. Lafferty, J., McCallum, A. and Pereira, F. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. 18th International Conf. on Machine Learning. Morgan Kaufmann, San Francisco, CA, 2001, 282-289.
19. Lin, D. Minipar; http://webdocs.cs.ualberta.ca/lindek/minipar.htm. 2007.
20. Liu, B., Sentiment analysis and subjectivity. Handbook of Natural Language Processing. N. Indurkhya and F.J. Damerau, eds. 2010.
21. Liu, B. Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies. Morgan & Claypool Publishers, 2012.
22. Loughran, T. and Mcdonald, B. When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. The Journal of Finance 66, 1 (2011), 35-65.
23. Mohammad, S.M. and Turney, P.D. 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 (2010).
24. Narayanan, R., Liu, B. and Choudhary, A. Sentiment analysis of conditional sentences. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (Singapore, 2009). Association for Computational Linguistics, 180-189.
25. Netzer, O., Feldman, R., Fresko, M. and Goldenberg, Y. Mine your own business: Market structure surveillance through text mining. Marketing Science, 2012.
26. Pang, B. and Lee, L. A Sentimental Education: Sentiment Analysis using Subjectivity Summarization based on minimum cuts. In Proceedings of the Association for Computational Linguistics (2004), 271-278.
27. Pang, B. and Lee, L. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval 2, 1-2 (2008), 1-135.
28. Pang, B., Lee, L. and Vaithyanathan, S. Thumbs up? Sentiment Classification using machine learning techniques. In Proceedings of EMNLP-02, 7th Conference on Empirical Methods in Natural Language Processing (Philadelphia, PA, 2002). Association for Computational Linguistics, Morristown, NJ, 79-86.
29. Peng, W. and Park, D.H. Generate adjective sentiment dictionary for social media sentiment analysis using constrained nonnegative matrix factorization. In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media (2011).
30. Popescu, A.-M. and Etzioni, O. Extracting product features and opinions from reviews. In Proceedings of Conference on Empirical Methods in Natural Language Processing (2005).
31. Qiu, G., Liu, B., Bu, J. and Chen, C. Opinion word expansion and target extraction through double propagation. Computational Linguistics 37, 1 (2011), 9-27.
32. Riloff, E. and Wiebe, J. Learning extraction patterns for subjective eExpressions. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (2003).
33. Stone, P. The general inquirer: A computer approach to content analysis. Journal of Regional Science 8, 1 (1968).
34. Taboada, M., J. Brooke, J., Tofiloski, M., Voll, K. and Stede, M. Lexicon-based methods for sentiment analysis. Computational Linguistics 37, 2 (2011), 267-307.
35. Tsur, O., Davidov, D. and Rappoport, A. A great catchy name: Semi-supervised recognition of sarcastic sentences in online product reviews. In Fourth International AAAI Conference on Weblogs and Social Media (2010).
36. Turney, P. Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In Proceedings of the Association for Computational Linguistics (2002), 417-424.
37. Wan, X. Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing (Honolulu, Hawaii, 2008). Association for Computational Linguistics, 553-561.
38. Wilson, T., Wiebe, J. and Hoffmann, P. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of the Human Language Technology Conference and the Conference on Empirical Methods in Natural Language Processing (2005), 347-354.
39. Wu, Y., Zhang, Q. Huang, X. and Wu, L. Phrase dependency parsing for opinion mining. In Proceedings of Conference on Empirical Methods in Natural Language Processing (2009).
40. Yu, H. and Hatzivassiloglou, V. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (2003).