acl acl2010 acl2010-141 acl2010-141-reference knowledge-graph by maker-knowledge-mining
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Author: Ahmed Hassan ; Dragomir Radev
Abstract: Automatically identifying the polarity of words is a very important task in Natural Language Processing. It has applications in text classification, text filtering, analysis of product review, analysis of responses to surveys, and mining online discussions. We propose a method for identifying the polarity of words. We apply a Markov random walk model to a large word relatedness graph, producing a polarity estimate for any given word. A key advantage of the model is its ability to accurately and quickly assign a polarity sign and magnitude to any word. The method could be used both in a semi-supervised setting where a training set of labeled words is used, and in an unsupervised setting where a handful of seeds is used to define the two polarity classes. The method is experimentally tested using a manually labeled set of positive and negative words. It outperforms the state of the art methods in the semi-supervised setting. The results in the unsupervised setting is comparable to the best reported values. However, the proposed method is faster and does not need a large corpus.
Alina Andreevskaia and Sabine Bergler. 2006. Mining wordnet for fuzzy sentiment: Sentiment tag extraction from wordnet glosses. In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2006). Carmen Banea, Rada Mihalcea, and Janyce Wiebe. 2008. A bootstrapping method for building subjectivity lexicons for languages with scarce resources. In Proceedings of the Sixth International Language Resources and Evaluation (LREC’08). Andrea Esuli and Fabrizio Sebastiani. 2005. Determining the semantic orientation of terms through gloss classification. In Proceedings of the 14th Conference on Information and Knowledge Management (CIKM 2005), pages 617–624. Andrea Esuli and Fabrizio Sebastiani. 2006. Sentiwordnet: A publicly available lexical resource for opinion mining. In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), pages 417–422. Vasileios Hatzivassiloglou and Kathleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, pages 174–18 1. Vasileios Hatzivassiloglou and Janyce Wiebe. 2000. Effects of adjective orientation and gradability on sentence subjectivity. In COLING, pages 299–305. Minqing Hu and Bing Liu. 2004. Mining and summarizing customer reviews. In KDD ’04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 168–177. Jaap Kamps, Maarten Marx, Robert J. Mokken, and Maarten De Rijke. 2004. Using wordnet to measure semantic orientations of adjectives. In National Institute for, pages 1115–1 118. Hiroshi Kanayama and Tetsuya Nasukawa. 2006. Fully automatic lexicon expansion for domainoriented sentiment analysis. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), pages 355– 363. Soo-Min Kim and Eduard Hovy. 2004. Determining the sentiment of opinions. In Proceedings of the 20th international conference on Computational Linguistics (COLING 2004), pages 1367–1373. 402 George A. Miller. 1995. Wordnet: a lexical database for english. Commun. ACM, 38(1 1):39–41 . Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi, and Toshikazu Fukushima. 2002. Mining product reputations on the web. In KDD ’02: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 341–349. Tetsuya Nasukawa and Jeonghee Yi. 2003. Sentiment analysis: capturing favorability using natural language processing. In K-CAP ’03: Proceedings of the 2nd international conference on Knowledge capture, pages 70–77. J. Norris. 1997. Markov chains. Cambridge University Press. Ana-Maria Popescu and Oren Etzioni. 2005. Extracting product features and opinions from reviews. In HLT ’05: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 339–346. Ellen Riloff and Janyce Wiebe. 2003. Learning extraction patterns for subjective expressions. In Proceedings of the 2003 conference on Empirical methods in natural language processing, pages 105–1 12. Philip Stone, Dexter Dunphy, Marchall Smith, and Daniel Ogilvie. 1966. The general inquirer: A computer approach to content analysis. The MIT Press. Martin Szummer and Tommi Jaakkola. 2002. Partially labeled classification with markov random walks. In Advances in Neural Information Processing Systems, pages 945–952. Hiroya Takamura, Takashi Inui, and Manabu Okumura. 2005. Extracting semantic orientations of words using spin model. InACL ’05: Proceedings ofthe 43rd Annual Meeting on Association for Computational Linguistics, pages 133–140. Richard M. Tong. 2001. An operational system for detecting and tracking opinions in on-line discussion. Workshop note, SIGIR 2001 Workshop on Operational Text Classification. Peter Turney and Michael Littman. 2003. Measuring praise and criticism: Inference of semantic orientation from association. ACM Transactions on Information Systems, 21:3 15–346. Peter D. Turney. 2002. Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In ACL ’02: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pages 417–424. Janyce Wiebe, Rebecca Bruce, Matthew Bell, Melanie Martin, and Theresa Wilson. 2001. A corpus study of evaluative and speculative language. In Proceedings of the Second SIGdial Workshop on Discourse and Dialogue, pages 1–10. Janyce Wiebe. 2000. Learning subjective adjectives from corpora. In Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, pages 735–740. Hong Yu and Vasileios Hatzivassiloglou. 2003. Towards answering opinion questions: separating facts from opinions and identifying the polarity ofopinion sentences. In Proceedings of the 2003 conference on Empirical methods in natural language processing, pages 129–136. Xiaojin Zhu, Zoubin Ghahramani, and John Lafferty. 2003. Semi-supervised learning using gaussian fields and harmonic functions. In In ICML, pages 912–919. 403