Opinion Mining

need to be organized

[http://dl.acm.org/citation.cfm?id=2000991]
[http://www.cs.uic.edu/~liub/FBS/AAAI-2011-tutorial-references.pdf]
[http://www.lrec-conf.org/proceedings/lrec2010/topics.html#Emotion_Recognition/Generation]


  1. Abbasi, A., & Chen, H. (2005). Identification and comparison of extremist-group Web forum messages using authorship analysis. IEEE Intelligent Systems, 20(5), 67-75.
  2. Abbasi, A., Chen, H., & Salem, A. (2008). Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums. ACM Transactions on Information Systems, 26(3).
  3. Adamic, L. A., & Glance, N. (2005). The political blogosphere and the 2004 US election: Divided they blog. Paper presented at the Proceedings of the 3rd international workshop on Link discovery (LinkKDD'05), Chicago, IL.
  4. Agrawal, R., Rajagopalan, S., Srikant, R., & Xu, Y. (2003, May 20-24, 2003). Mining newsgroups using networks arising from social behavior. Paper presented at the Proceedings of the 12th International Conference on World Wide Web, Budapest, Hungary.
  5. Andreevskaia, A., & Bergler, S. (2006). Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses. Paper presented at the Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06), Trento, Italy.
  6. Aue, A., & Gamon, M. (2005, September 21-23, 2005). Customizing sentiment classifiers to new domains: A case study. Paper presented at the Proceedings of International Conference Recent Advances in Natural Language Processing (RANLP-2005), Borovets, Bulgaria.
  7. Baron, F., & Hirst, G. (2004, March 22-24, 2004). Collocations as cues to semantic orientation. Paper presented at the Proceedings of the AAAI Spring Symposium on Exploring Attitude and Affect in Text: Theories and Applications, Stanford, CA.
  8. Baroni, M., & Vegnaduzzo, S. (2004). Identifying subjective adjectives through Web-based mutual information. Paper presented at the Proceedings of the 7th Konferenz zur Verarbeitung Natürlicher Sprache (German Conference on Natural Language Processing – KONVENS’04), Vienna, Austria.
  9. Bethard, S., Yu, H., Thornton, A., Hatzivassiloglou, V., & Jurafsky, D. (2006). Extracting opinion propositions and opinion holders using syntactic and lexical cues. In J. G. Shanahan, Y. Qu & J. Wiebe (Eds.), Computing attitude and affect in text: Theory and applications (Vol. 20, pp. 125-141).
  10. Bloom, K., Garg, N., & Argamon, S. (2007). Extracting appraisal expressions. Paper presented at the Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL HLT), Rochester, NY.
  11. Breck, E., Choi, Y., & Cardie, C. (2007, January 6-12). Identifying expressions of opinion in context. Paper presented at the Proceedings of the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India.
  12. Bruce, R., & Wiebe, J. (1999). Recognizing subjectivity: A case study in manual tagging. Natural Language Engineering, 5, 187-205.
  13. Chesley, P., Vincent, B., Xu, L., & Srihari, R. K. (2006, March 27-29, 2006). Using verbs and adjectives to automatically classify blog sentiment. Paper presented at the Proceedings of AAAI-CAAW-06, the Spring Symposia on Computational Approaches to Analyzing Weblogs Stanford University, CA.
  14. Chklovski, T. (2006). Deriving quantitative overviews of free text assessments on the Web. Paper presented at the Proceedings of the 11th International Conference on Intelligent User Interfaces, Sydney, Australia.
  15. Choi, Y., Cardie, C., Riloff, E., & Patwardhan, S. (2005). Identifying sources of opinions with conditional random fields and extraction patterns. Paper presented at the Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada.
  16. Conrad, J. G., & Schilder, F. (2007). Opinion mining in legal blogs. Paper presented at the Proceedings of the 11th International Conference on Artificial Intelligence and Law, Stanford, CA.
  17. Cui, H., Mittal, V. O., & Datar, M. (2006, July 16-20, 2006). Comparative experiments on sentiment classification for online product reviews. Paper presented at the Proceedings of the 21st National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference, Boston, MA.
  18. Dave, K., Lawrence, S., & Pennock, D. M. (2003, May 20-24, 2003). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. Paper presented at the Proceedings of WWW '03: The 12th International Conference on World Wide Web, Budapest, Hungary.
  19. Ding, X., Liu, B., & Yu, P. S. (2008, Feb 11-12, 2008). A holistic lexicon-based approach to opinion mining. Paper presented at the Proceedings of the International Conference on Web Search and Web Data Mining, Palo Alto, CA.
  20. Eckle-Kohler, J., Kohler, M., & Mehnert, J. (2005). Automatic recognition of German news focusing on future-directed beliefs and intentions. Computer Speech and Language, 22(4), 394-414.
  21. Efron, M. (2004, October 21-24). Cultural orientation: Classifying subjective documents by cocitation analysis. Paper presented at the Proceedings of AAAI Fall Symposium on Style and Meaning in Language, Art, and Music, Washington, D.C.
  22. Esuli, A., & Sebastiani, F. (2005, October 31- November 05, 2005). Determining the semantic orientation of terms through gloss classification. Paper presented at the Proceedings of the 14th ACM International Conference on Information and Knowledge Management, Bremen, Germany.
  23. Esuli, A., & Sebastiani, F. (2006, April 3-7, 2006). Determining term subjectivity and term orientation for opinion mining. Paper presented at the Proceedings of the 11th Meeting of the European Chapter of the Association for Computational Linguistics (EACL 2006) Trento, Italy.
  24. Esuli, A., & Sebastiani, F. (2006, May 22-28, 2006). Sentiwordnet: A publicly available lexical resource for opinion mining. Paper presented at the Proceedings of the 5th Conference on Language Resources and Evaluation (LREC-06), Genoa, Italy.
  25. Fillmore, C. J., & Baker, C. F. (2001). Frame semantics for text understanding. Paper presented at the Proceedings of WordNet and Other Lexical Resources Workshop, Pittsburgh, PA.
  26. Finn, A., Kushmerick, N., & Smyth, B. (2002). Genre classification and domain transfer for information filtering. Lecture Notes in Computer Science, 2291, 349-352.
  27. Gamon, M. (2004, August 23-27, 2004). Sentiment classification on customer feedback data: Noisy data, large feature vectors, and the role of linguistic analysis. Paper presented at the Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland.
  28. Gamon, M., & Aue, A. (2005). Automatic identification of sentiment vocabulary: Exploiting low association with known sentiment terms. Paper presented at the Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in NLP, Ann Arbor, MI.
  29. Gamon, M., Aue, A., Corston-Oliver, S., & Ringger, E. (2005). Pulse: Mining customer opinions from free text. In Advances in Intelligent Data Analysis VI (pp. 121-132).
  30. Glance, N., Hurst, M., Nigam, K., Siegler, M., Stockton, R., & Tomokiyo, T. (2005, August 21-24, 2005). Deriving marketing intelligence from online discussion. Paper presented at the Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, Chicago, IL.
  31. Grefenstette, G., Qu, Y., Shanahan, J. G., & Evans, D. A. (2004, April 26-28). Coupling niche browsers and affect analysis for an opinion mining application. Paper presented at the Proceedings of the 7th International RIAO Conference (Recherche d'Information Assistée par Ordinateur), Avignon, FR.
  32. Grishman, R. (1986). Computational linguistics: An introduction (studies in natural language processing). New York, NY: Cambridge University Press.
  33. Hancock, J. T., Landrigan, C., & Silver, C. (2007). Expressing emotion in text-based communication. Paper presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, San Jose, CA.
  34. Hannah, D., Macdonald, C., Peng, J., He, B., & Ounis, I. (2007). University of Glasgow at TREC 2007: Experiments in blog and enterprise tracks with terrier. Proceedings of the Sixteenth Text REtrieval Conference (TREC 2007).
  35. Hatzivassiloglou, V., & McKeown, K. R. (1997, July 07-12, 1997). Predicting the semantic orientation of adjectives. Paper presented at the Proceedings of the Eighth Conference on European Chapter of the Association for Computational Linguistics, Madrid, Spain.
  36. Hatzivassiloglou, V., & Wiebe, J. (2000, July 31-August 04, 2000). Effects of adjective orientation and gradability on sentence subjectivity. Paper presented at the Proceedings of the 18th Conference on Computational Linguistics, Saarbrücken, Germany.
  37. Hearst, M. A. (1992). Direction-based text interpretation as an information access refinement In P. Jacobs (Ed.), Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval (pp. 11-18). Mahwah, NJ: Lawrence Erlbaum Associates.
  38. Holzman, L. E., & Pottenger, W. M. (2003). Classification of emotions in Internet chat: An application of machine learning using speech phonemes. (P. L. U. Bethlehem o. Document Number)
  39. Hsu, C., Chang, C., & Lin, C. (2003). A practical guide to support vector classification (Technical Report). (D. o. C. S. a. I. E. National Taiwan University o. Document Number)
  40. Hu, M., & Liu, B. (2004). Mining opinion features in customer reviews. Paper presented at the Proceedings of Nineteeth National Conference on Artificial Intellgience (AAAI-2004), San Jose, CA.
  41. Hunston, S., & Thompson, G. (2000). Evaluation: An introduction. In S. Hunston & G. Thompson (Eds.), Evaluation in text: Authorial stance and the construction of discourse: Oxford: Oxford University Press.
  42. Hurst, M., & Nigam, K. (2004, January 21-22, 2004). Retrieving topical sentiments from online document collections. Paper presented at the Proceedings of the 11th Conference on Document Recognition and Retrieval, San Jose, CA.
  43. Joachims, T. (1999). Making large-scale SVM learning practical. In B. Schölkopf, C. Burges & A. Smola (Eds.), Advances in kernel methods: Support vector learning (pp. 169 - 184). Cambridge, MA: MIT-Press.
  44. Joachims, T. (2001). A statistical learning model of text classification for support vector machines. Paper presented at the Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, LA.
  45. Jurafsky, D., & Martin, J. H. (2008). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition (2nd ed.): Upper Saddle River, N.J.: Pearson Prentice-Hall.
  46. Kamps, J., Marx, M., Mokken, R. J., & Rijke, M. D. (2004). Using WordNet to measure semantic orientation of adjectives. Paper presented at the Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC'04), Lisbon, Portugal.
  47. Kanayama, H., & Nasukawa, T. (2006). Fully automatic lexicon expansion for domain-oriented sentiment analysis. Paper presented at the Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), Sydney, Australia.
  48. Karlgren, J., & Cutting, D. (1994). Recognizing text genres with simple metrics using discriminant analysis. Paper presented at the Proceedings of the 15th Conference on Computational Linguistics, Kyoto, Japan.
  49. Kim, S.-M., & Hovy, E. (2004, August 23-27, 2004). Determining the sentiment of opinions. Paper presented at the Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland.
  50. Kim, S.-M., & Hovy, E. (2005). Automatic detection of opinion bearing words and sentences. Paper presented at the Companion Volume to the Proceedings of IJCNLP-05, the Second International Joint Conference on Natural Language Processing, Jeju Island, Republic of Korea.
  51. Kim, S.-M., & Hovy, E. (2005). Identifying opinion holders for question answering in opinion texts. Paper presented at the Proceedings of AAAI Workshop on Question Answering in Restricted Domains, Pittsburgh, PA.
  52. Kim, S.-M., & Hovy, E. (2006). Automatic identification of pro and con reasons in online reviews. Proceedings of the COLING/ACL on Main conference poster sessions, 483-490.
  53. Kim, S.-M., & Hovy, E. (2006, July 22, 2006). Extracting opinions, opinion holders, and topics expressed in online news media text. Paper presented at the Proceedings of ACL/COLING Workshop on Sentiment and Subjectivity in Text, Sydney, Australia.
  54. Kobayashi, N., Inui, K., Matsumoto, Y., Tateishi, K., & Fukushima, T. (2004, March 22-24, 2004). Collecting evaluative expressions for opinion extraction. Paper presented at the Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP), Hainan Island, China.
  55. Koppel, M., & Shtrimberg, I. (2006). Good news or bad news? Let the market decide. In Y. Q. James G. Shanahan, Janyce Wiebe (Ed.), Computing attitude and affect in text: Theory and applications (pp. 297-301): Dordrecht: Springer.
  56. Ku, L.-W., & Chen, H.-H. (2007). Mining opinions from the Web: Beyond relevance retrieval. Journal of the American Society for Information Science and Technology, 58(12), 1838-1850.
  57. Levin, B. (1993). English verb classes and alternations. Chicago, IL: University of Chicago Press.
  58. Li, Y., Bontcheva, K., & Cunningham, H. (2007, May 15-18, 2007). Experiments of opinion analysis on two corpora MPQA and NTCIR-6. Paper presented at the Proceedings of the 6th NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retrieval, Question Answering and Cross-Lingual Information Access, Tokyo, Japan.
  59. Lin, D. (1998). Automatic retrieval and clustering of similar words. Paper presented at the Proceedings of the 17th international conference on Computational linguistics, Montreal, Quebec, Canada.
  60. Lin, W.-H., Wilson, T., Wiebe, J., & Hauptmann, A. (2006). Which side are you on? Identifying perspectives at the document and sentence levels. Paper presented at the Proceedings of Tenth Conference on Natural Language Learning (CoNLL’06), New York, US.
  61. Liu, B. (2007). Web data mining: Exploring hyperlinks, contents and usage data (data-centric systems and applications). Berlin: Springer.
  62. Liu, B., Hu, M., & Cheng, J. (2005). Opinion observer: Analyzing and comparing opinions on the Web. Paper presented at the Proceedings of the 14th International Conference on World Wide Web, New York, NY.
  63. Liu, H., Lieberman, H., & Selker, T. (2003, January 12-15, 2003). A model of textual affect sensing using real-world knowledge. Paper presented at the Proceedings of the 8th International Conference on Intelligent User Interfaces, Miami, FL.
  64. Macdonald, C., Ounis, I., & Soboroff, I. (2007). Overview of the TREC-2007 blog track. Proceedings of the 16th Text REtrieval Conference (TREC 2007).
  65. Malouf, R., & Mullen, T. (2008). Taking sides: User classification for informal online political discourse. Internet Research, 18(2), 177-190.
  66. Manning, C. D., Raghavan, P., & Schutze, H. (2008). Introduction to information retrieval. New York, NY: Cambridge University Express.
  67. Manning, C. D., & Schutze, H. (1999). Foundations of statistical natural language processing (1st ed.). Cambridge, MA: The MIT Press.
  68. Marcus, M. P., Marcinkiewicz, M. A., & Santorini, B. (1993). Building a large annotated corpus of English: The penn treebank. Computational Linguistics, 19(2), 313-330.
  69. Martin, J. R., & White, P. R. R. (2005). The language of evaluation: The appraisal framework. New York: Palgrave Mmacmillan.
  70. McDonald, R., Hannan, K., Neylon, T., Wells, M., & Reynar, J. (2007). Structured models for fine-to-coarse sentiment analysis. Paper presented at the Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, Prague, Czech Republic.
  71. Mei, Q., Ling, X., Wondra, M., Su, H., & Zhai, C. (2007, May 08-12, 2007). Topic sentiment mixture: Modeling facets and opinions in Weblogs. Paper presented at the Proceedings of the 16th International Conference on World Wide Web, Banff, Alberta, Canada.
  72. Miller, G. A., Beckwith, R., Fellbaum, C., Gross, D., & Miller, K. J. (1990). Introduction to WordNet: An on-line lexical database. International Journal of Lexicography, 3(4), 235-244.
  73. Mishne, G. (2005). Experiments with mood classification in blog posts. Paper presented at the Proceedings of Style2005 - the 1st Workshop on Stylistic Analysis Of Text For Information Access, at SIGIR 2005, Salvador, Bahia, Brazil.
  74. Mullen, T., & Collier, N. (2004). Sentiment analysis using support vector machines with diverse information sources. Paper presented at the Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, Barcelona, Spain.
  75. Na, J.-C., Khoo, C. S. G., Chan, S., & Hamzah, N. B. (2005). Sentiment-based search in digital libraries. Paper presented at the Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries.
  76. Nasukawa, T., & Yi, J. (2003, October 23-25, 2003). Sentiment analysis: Capturing favorability using natural language processing. Paper presented at the Proceedings of the 2nd International Conference on Knowledge Capture, Sanibel Island, FL.
  77. Ng, V., Dasgupta, S., & Arifin, S. M. N. (2006). Examining the role of linguistic knowledge sources in the automatic identification and classification of reviews. Paper presented at the Proceedings of the COLING/ACL on Main conference poster sessions, Sydney, Australia.
  78. Nigam, K., & Hurst, M. (2004, March 22-24, 2004). Towards a robust metric of opinion. Paper presented at the Proceedings of the AAAI Spring Symposium on Exploring Attitude and Affect in Text, Stanford, CA.
  79. Nigam, K., & Hurst, M. (2006). Towards a robust metric of polarity. In Computing attitude and affect in text: Theory and applications (Vol. 20, pp. 265-279): Dordrecht, Netherlands: Springer.
  80. Niu, Y., Zhu, X., Li, J., & Hirst, G. (2005, October 22-26, 2005). Analysis of polarity information in medical text. Paper presented at the Proceedings of the American Medical Informatics Association 2005 Annual Symposium, Washington, DC.
  81. Ounis, I., Rijke, M. d., Macdonald, C., Mishne, G., & Soboroff, I. (2007). Overview of the TREC-2006 blog track. Proceedings of the 15th Text REtrieval Conference.
  82. Pang, B., & Lee, L. (2004, July 21-26, 2004). A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. Paper presented at the Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, Barcelona, Spain.
  83. Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135.
  84. Pang, B., Lee, L., & Vaithyanathan, S. (2002, July 6-7, 2002). Thumbs up? Sentiment classification using machine learning techniques. Paper presented at the Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, Philadelphia, PA.
  85. Picard, R. W. (1997). Affective computing. Cambridge, MA: The MIT Press.
  86. Porter, M. (1980). An algorithm for suffix stripping program. Program, 14(3), 130-137.
  87. Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (1985). A comprehensive grammar of the English language. London: Longman.
  88. Riloff, E., & Jones, R. (1999). Learning dictionaries for information extraction by multi-level bootstrapping. Paper presented at the Proceedings of the Sixteenth National Conference on Artificial Intelligence, Orlando, FL.
  89. Riloff, E., Patwardhan, S., & Wiebe, J. (2006). Feature subsumption for opinion analysis. Paper presented at the Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP-2006), Sydney, Australia.
  90. Riloff, E., & Wiebe, J. (2003, July 11-12, 2003). Learning extraction patterns for subjective expressions. Paper presented at the Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, Sapporo, Japan.
  91. Riloff, E., Wiebe, J., & Phillips, W. (2005, July 9-13, 2005). Exploiting subjectivity classification to improve information extraction. Paper presented at the Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-2005), Pittsburgh, PA.
  92. Riloff, E., Wiebe, J., & Wilson, T. (2003, May 27-June 1, 2003). Learning subjective nouns using extraction pattern bootstrapping. Paper presented at the Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, Edmonton, Canada.
  93. Schler, J., Koppel, M., Argamon, S., & Pennebaker, J. (2006). Effects of age and gender on blogging. Paper presented at the AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, Menlo Park, CA.
  94. Sebastiani, F. (2006). Classification of automatic text In K. Brown (Ed.), The encyclopedia of language and linguistics (2nd ed., Vol. 14, pp. 457-462). Amsterdam, NL: Elsevier Science Publishers.
  95. Seki, Y., Eguchi, K., Kando, N., & Aono, M. (2005). Multi-document summarization with subjectivity analysis at DUC 2005. Paper presented at the Proceeding of the Document Understanding Conference Workshop 2005 (DUC 2005) at the Human Language Technology Conference/Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP 2005), Vancouver, B.C., Canada.
  96. Seki, Y., Eguchi, K., Kando, N., & Aono, M. (2006). Opinion-focused summarization and its analysis at DUC 2006. Paper presented at the Proceedings of the Document Understanding Conference 2006 (DUC 2006), Brooklyn, NY.
  97. Seki, Y., Evans, D. K., Ku, L.-W., Chen, H.-H., Kando, N., & Lin, C.-Y. (2007, May 15-18, 2007). Overview of opinion analysis pilot task at NTCIR-6. Paper presented at the Proceedings of the 6th NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retrieval, Question Answering and Cross-Lingual Information Access, Tokyo, Japan.
  98. Sifry, D. (2007). The state of the live Web. Retrieved September 12, 2008, from http://technorati.com/weblog/2007/04/328.html
  99. Srihari, R. k., Li, W., Cornell, T., & Niu, C. (2008). Infoxtract: A customizable intermediate level information extraction engine. Natural Language Engineering, 14(1), 33-69.
  100. Srihari, R. K., Li, W., Niu, C., & Cornell, T. (2003, May 27-June 01, 2003). Infoxtract: A customizable intermediate level information extraction engine. Paper presented at the HLT-NAACL 2003 Workshop on Software Engineering and Architecture of Language Technology Systems, Edmonton, Canada.
  101. Stone, P. J. (1997). Thematic text analysis: New agendas for analyzing text content. In C. Roberts (Ed.), Text analysis for the social sciences. Mahwah NJ: Lawrence Erlbaum Associates.
  102. Stoyanov, V., Cardie, C., & Wiebe, J. (2005, October 06-08, 2005). Multi-perspective question answering using the OpQA corpus. Paper presented at the Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada.
  103. Taboada, M., Anthony, C., & Voll, K. (2006). Methods for creating semantic orientation databases. Paper presented at the Proceeding of LREC-06, the 5th International Conference on Language Resources and Evaluation, Genoa, Italy.
  104. Takamura, H., Inui, T., & Okumura, M. (2005). Extracting semantic orientations of words using spin model. Paper presented at the Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, Ann Arbor, Michigan.
  105. Takamura, H., Inui, T., & Okumura, M. (2006). Latent variable models for semantic orientations of phrases. Paper presented at the Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL).
  106. Takamura, H., Inui, T., & Okumura, M. (2007). Extracting semantic orientations of phrases from dictionary. Paper presented at the Proceedings of the Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT2007), Rochester NY, USA.
  107. Thelen, M., & Riloff, E. (2002). A bootstrapping method for learning semantic lexicons using extraction pattern contexts. Paper presented at the ACL-02 Conference on Empirical Methods in Natural Language Processing, Philadelphia, PA.
  108. Thomas, M., Pang, B., & Lee, L. (2006, July 22-23, 2006). Get out the vote: Determining support or opposition from congressional floor-debate transcripts. Paper presented at the Proceedings of 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), Sydney, Australia.
  109. Tokuhisa, R., & Terashima, R. (2006, July 15-16, 2006). Relationship between utterances and enthusiasm in non-task-oriented conversational dialogue. Paper presented at the Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue, Sydney, Australia.
  110. Tsou, B. K. Y., Yuen, R. W. M., Kwong, O. Y., Lai, T. B. Y., & Wong, W. L. (2005, May 2-4, 2005). Polarity classification of celebrity coverage in the Chinese press. Paper presented at the Proceedings of the International Conference on Intelligence Analysis, McLean, VA.
  111. Turney, P. D. (2002). Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews. Paper presented at the Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Philadelphia, PA.
  112. Turney, P. D., & Littman, M. L. (2002). Unsupervised learning of semantic orientation from a hundred-billion-word corpus (Tech report No. ERB-1094): National Research Council Canada, Institute for Information Technology. (N. R. C. Canada o. Document Number)
  113. Turney, P. D., & Littman, M. L. (2003). Measuring praise and criticism: Inference of semantic orientation from association. ACM Transactions on Information Systems (TOIS), 21(4), 315-346.
  114. Vechtomova, O. (2007). Using subjective adjectives in opinion retrieval from blogs. Proceedings of the Sixteenth Text REtrieval Conference (TREC 2007).
  115. Whitelaw, C., Garg, N., & Argamon, S. (2005, October 31-November 05). Using appraisal groups for sentiment analysis. Paper presented at the Proceedings of the 14th ACM international conference on Information and knowledge management, Bremen, Germany.
  116. Whitelaw, C., Garg, N., & Argamon, S. (2005). Using appraisal taxonomies for sentiment analysis. Paper presented at the Proceedings of MCLC-05, the 2nd Midwest Computational Linguistic Colloquium (MCLC 2005), Columbus, Ohio.
  117. Wiebe, J. (1994). Tracking point of view in narrative. Computational Linguistics, 20(2), 233-287.
  118. Wiebe, J. (2000, July 30-August 03, 2000). Learning subjective adjectives from corpora. Paper presented at the Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000), Austin, TX.
  119. Wiebe, J., Breck, E., Buckley, C., Cardie, C., Davis, P., Fraser, B., et al. (2003). Recognizing and organizing opinions expressed in the world press. In AAAI Spring Symposium on New Directions in Question Answering (pp. 24-66). Stanford, CA: Stanford University.
  120. Wiebe, J., Bruce, R., Bell, M., Martin, M., & Wilson, T. (2001, September 01-02, 2001). A corpus study of evaluative and speculative language. Paper presented at the Proceedings of the Second SIGdial Workshop on Discourse and Dialogue, Aalborg, Denmark.
  121. Wiebe, J., Bruce, R., & O'Hara, T. P. (1999, June 20-26, 1999). Development and use of a gold-standard data set for subjectivity classifications. Paper presented at the Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics on Computational Linguistics, College Park, MD.
  122. Wiebe, J., & Mihalcea, R. (2006, July 17-18, 2006). Word sense and subjectivity. Paper presented at the Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL, Sydney, Australia.
  123. Wiebe, J., & Riloff, E. (2005, Feb 13-19, 2005). Creating subjective and objective sentence classifiers from unannotated texts. Paper presented at the Proceedings of the 6th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2005). , Mexico City, Mexico.
  124. Wiebe, J., & Wilson, T. (2002). Learning to disambiguate potentially subjective expressions. Proceedings of the 6th Conference on Natural Language Learning, 20, 1-7.
  125. Wiebe, J., Wilson, T., & Bell, M. (2001). Identifying collocations for recognizing opinions. Paper presented at the Proceedings of the ACL-01 Workshop on Collocation: Computational Extraction, Analysis, and Exploitation, Toulouse, France.
  126. Wiebe, J., Wilson, T., Bruce, R., Bell, M., & Martin, M. (2004). Learning subjective language. Computational Linguistics, 30(3), 277-308.
  127. Wiebe, J., Wilson, T., & Cardie, C. (2005). Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(2), 165-210.
  128. Wilson, T., Pierce, D. R., & Wiebe, J. (2003). Identifying opinionated sentences. Paper presented at the Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations, Edmonton, Canada.
  129. Wilson, T., Wiebe, J., & Hoffmann, P. (2005). Recognizing contextual polarity in phrase-level sentiment analysis. Paper presented at the Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language, Vancouver, Canada.
  130. Wilson, T., Wiebe, J., & Hwa, R. (2004, July 25-29, 2004). Just how mad are you? Finding strong and weak opinion clauses. Paper presented at the Proceedings of the 19th National Conference on Artificial Intelligence (AAAI‐2004), San Jose, CA.
  131. Wilson, T., Wiebe, J., & Hwa, R. (2006). Recognizing strong and weak opinion clauses. Computational Intelligence, 22(2), 73–99.
  132. Yaacov, C. (1988). Looking for needles in a haystack or, locating interesting expressions in large textual databases. Paper presented at the In Proceedings of the International Conference on User-Oriented Content-Based Text and Image Handling, Cambridge, MA.
  133. Yang, C., Gao, H., & Chen, S. (2007). 以部落格語料進行情緒趨勢分析. Paper presented at the Proceedings of the 19th Conference on Computational Linguistics and Speech Processing, Taipei, Taiwan.
  134. Yang, K., Yu, N., & Zhang, H. (2007). WIDIT in TREC-2007 Blog track: Combining lexicon-based methods to detect opinionated blogs. Proceedings of the 16th Text REtrieval Conference (TREC 2007).
  135. Yi, J., Nasukawa, T., Bunescu, R., & Niblack, W. (2003, November 19-22, 2003). Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques. Paper presented at the Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM-2003) Melbourne, FL.
  136. Yi, J., & Niblack, W. (2005, April 05-08, 2005). Sentiment mining in WebFountain. Paper presented at the Proceedings of the 21st International Conference on Data Engineering (ICDE-2005), Tokyo, Japan.
  137. Yu, B. (2006). An evaluation of text classification methods for literary study. University of Illinois at Urbana-Champaign.
  138. Yu, H., & Hatzivassiloglou, V. (2003). Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, 10, 129-136.
  139. Zhang, L., Barnden, J. A., Hendley, R. J., & Wallington, A. M. (2006, July 22, 2006). Exploitation in affect detection in open-ended improvisational text. Paper presented at the Proceedings of Workshop on Sentiment and Subjectivity in Text, Sydney, Australia.
  140. Zhang, W., & Yu, C. (2006). UIC at TREC 2006 blog track. Proceedings of the 15th Text REtrieval Conference (TREC 2006).
  141. Zhang, W., & Yu, C. (2007). UIC at TREC 2007 blog track. Proceedings of the 16th Text REtrieval Conference (TREC 2007).
  142. Zhang, W., Yu, C., & Meng, W. (2007). Opinion retrieval from blogs. Paper presented at the Proceedings of the 16th ACM Conference on Information and Knowledge Management, Lisbon, Portugal.
  143. Zheng, R., Li, J., Chen, H., & Huang, Z. (2006). A framework for authorship identification of online messages: Writing-style features and classification techniques. Journal of the American Society for Information Science and Technology, 57(3), 378-393.
  144. Zhou, G., Joshi, H., & Bayrak, C. (2007). Topic categorization for relevancy and opinion detection. Proceedings of the 16th Text REtrieval Conference (TREC 2007).
Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3.0 License