Jack G. Conrad
Frank Schilder
ABSTRACT
We perform a survey into the scope and utility of opinion mining in legal Weblogs (a.k.a. blawgs). The number of 'blogs' in the legal domain is growing at a rapid pace and many potential applications for opinion detection and monitoring are arising as a result. We summarize current approaches to opinion mining before describing different categories of blawgs and their potential impact on the law and the legal profession. In addition to educating the community on recent developments in the legal blog space, we also conduct some introductory opinion mining trials. We first construct a Weblog test collection containing blog entries that discuss legal search tools. We subsequently examine the performance of a language modeling approach deployed for both subjectivity analysis (i.e., is the text subjective or objective?) and polarity analysis (i.e., is the text affirmative or negative towards its subject?). This work may thus help establish early baselines for these core opinion mining tasks.
- M. Baroni and S. Vegnaduzzo. Identifying subjective adjectives through web-based mutual information. In E. Buchberger, editor, In Proceedings of the Conference for the Processing of Natural Language and Speech (KONVENS), pages 17--24, Vienna, Austria, September 2004.Google Scholar
- K. Dave, S. Lawrence, and D. M. Pennock. Mining the peanut gallery: Opinon extraction and semantic classification of product reviews. In Proceedings of the International World Wide Web Conference, Budapest, Hungary, May 2003. Google ScholarDigital Library
- A. Esuli and F. Sebastiani. Determining term subjectivity and term orientation for opinion mining. In Proceedings EACL-06, the 11th Conference of the European Chapter of the Association for Computational Linguistics, Trento, Italy, 2006.Google Scholar
- A. Esuli and F. Sebastiani. Sentiwordnet: A publicly available lexical resource for opinion mining. In Proceedings of LREC-06, the 5th Conference on Language Resources and Evaluation, Genova, Italy, 2006.Google Scholar
- M. Gamon, A. Aue, S. Corston-Oliver, and E. Ringger. Pulse: Mining customer opinions from free text. In Proceedings of IDA-05, the 6th International Symposium on Intelligent Data Analysis, Lecture Notes in Computer Science, Madrid, Spain, 2005. Springer-Verlag. Google ScholarDigital Library
- V. Hatzivassiloglou and K. R. McKeown. Predicting the semantic orientation of adjectives. In Proceedings of ACL-97, 35th Annual Meeting of the Association for Computational Linguistics, pages 174--181, Madrid, Spain, 1997. Association for Computational Linguistics. Google ScholarDigital Library
- V. Hatzivassiloglou and J. M. Wiebe. Effects of adjective orientation and gradability on sentence subjectivity. In Proceedings of COLING-00, 18th International Conference on Computational Linguistics, pages 299--305, Saarbrücken, Germany, 2000. Morgan Kaufmann. Google ScholarDigital Library
- M. Hu and B. Liu. Mining opinion features in customer reviews. In Proceedings of AAAI-04, the 19th National Conference on Artificial Intellgience, San Jose, California, 2004. Google ScholarDigital Library
- M. Hu and B. Lu. Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 168--177, Seattle, Washington, August 2004. ACM Press. Google ScholarDigital Library
- J. Kamps, M. Marx, R. J. Mokken, and M. de Rijke. Words with attitude. In Proceedings of the 1st International Conference on Global WordNet, pages 332--341, Mysore, India, January 2002.Google Scholar
- S.-M. Kim and E. Hovy. Determining the sentiment of opinions. In Proceedings COLING-04, the Conference on Computational Linguistics, Geneva, Switzerland, 2004. Google ScholarDigital Library
- M.-F. Moens. A retrieval model for accessing legislation. In Proceedings of the Tenth International Conference on Artificial Intelligence and Law (ICAIL 2005), pages 141--145, Bologna, Italy, June 2005. ACM Press. Google ScholarDigital Library
- S. Morinaga, K. Yamanishi, K. Tateishi, and T. Fukushima. Mining product reputations on the web. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Management Discovery and Data Mining, pages 341--349, Edmonton, Alberta Canada, July 2002. ACM Press. Google ScholarDigital Library
- B. Pang and L. Lee. Sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proceedings of the ACL 2004, pages 271--278, Madrid, Spain, 2004. Association for Computational Linguistics, ACL Press. Google ScholarDigital Library
- B. Pang and L. Lee. Seeing stars: Exploting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 2005. Google ScholarDigital Library
- B. Pang, L. Lee, and S. Vaithyanathan. Thumbs up? sentiment classification using machine learning techniques. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-02), pages 79--86, Philadelphia, Pennsylvania, July 2002. ACL Press. Google ScholarDigital Library
- J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In Proceedings of the 21st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR98), pages 275--281, Melbourne, Australia, August 1998. ACM Press. Google ScholarDigital Library
- E. Riloff and J. Wiebe. Learning extraction patterns for subjective expressions. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-03), pages 105--112, Sapporo, Japan, July 2003. ACL Press. Google ScholarDigital Library
- J. Shanahan, Y. Qu, and J. Wiebe, editors. Computing Attitude and Affect in Text. Springer, 2006. Collected Works. Google ScholarDigital Library
- H. Takamura, T. Inui, and M. Okumura. Extracting emotional polarity of words using spin model. In Proceedings of ACL-05, 43rd Annual Meeting of the Association for Computational Linguistics, Ann Arbor, Michigan, 2005. Association for Computational Linguistics. Google ScholarDigital Library
- P. D. Turney. Thumbs up or thumbs down? In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pages 417--424, Philadelphia, Pennsylvania, July 2002. ACL Press. Google ScholarDigital Library
- P. D. Turney and M. L. Littman. Measuring praise and criticism: Inference of semantic orientation from association. In G. Marchionini, editor, Transactions on Information Systems (TOIS), volume 21, no. 4, pages 315--346, New York, October 2003. ACM Press. Google ScholarDigital Library
- S. Vegnaduzzo. Acquisition of subjective adjectives with limited resources. In J. G. Shanahan, J. Wiebe, and Y. Qu, editors, Proceedings of the AAAI Spring Symposium on Exploring Attitude and Affect in Text: Theories and Applications, Stanford, US, 2004.Google Scholar
- C. Whitelaw, N. Garg, and S. Argamon. Using appraisal groups for sentiment analysis. In O. Herzog, H.-J. Schek, N. Fuhr, A. Chowdhury, and W. Teiken, editors, Proceedings of the 14th ACM International Conference on Information and Knowledge Management (CIKM05), pages 625--631, Bremen, Germany, November 2005. ACM Press. Google ScholarDigital Library
- J. Wiebe. Learning subjective adjectives from corpora. In Proceedings of AAAI-00, 17th Conference of the American Association for Artificial Intelligence, pages 735--740, Austin, Texas, 2000. AAAI Press / The MIT Press. Google ScholarDigital Library
- J. Wiebe, E. Breck, C. Buckley, C. Cardie, P. Davis, B. Fraser, D. Litman, D. Pierce, E. Riloff, T. Wilson, D. Day, and M. Maybury. Recognizing and organizing opinions expressed in the world press. In Proceedings of the 2003 AAAI Spring Symposium on New Directions in Question Answering. AAAI Press, 2003.Google Scholar
- J. Wiebe and E. Riloff. Creating subjective and objective sentence classifiers from unannotated texts. In Proceeding of CICLing-05, International Conference on Intelligent Text Processing and Computational Linguistics., volume 3406 of Lecture Notes in Computer Science, pages 475--486, Mexico City, Mexico, 2005. Springer-Verlag. Google ScholarDigital Library
- J. Wiebe, T. Wilson, and C. Cardie. Annotating expressions of opinions and emotions in language. In Language Resources Evaluation, volume 29, pages 165--210, the Netherlands, 2005. Kluwer Academic Publishers.Google Scholar
- T. Wilson, J. Wiebe, and P. Hoffmann. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of Human Language Technologies Conference/Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP 2005), pages 347--354, Vancouver, BC Canada, October 2005. ACL Press. Google ScholarDigital Library
- T. Wilson, J. Wiebe, and R. Hwa. Just how mad are you? finding strong and weak opinion clauses. In D. L. McGuinness and G. Ferguson, editors, Proceedings of the 19th National Conference on Artificial Intelligence, 16th Conference on Innovative Applications of AI, pages 761--769. American Association of Artificial Intelligence (AAAI), AAAI Press / The MIT Press, July 2004. Google ScholarDigital Library
Index Terms
- Opinion mining in legal blogs
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