acl acl2013 acl2013-121 acl2013-121-reference knowledge-graph by maker-knowledge-mining
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Author: Arjun Mukherjee ; Bing Liu
Abstract: Online discussion forums are a popular platform for people to voice their opinions on any subject matter and to discuss or debate any issue of interest. In forums where users discuss social, political, or religious issues, there are often heated debates among users or participants. Existing research has studied mining of user stances or camps on certain issues, opposing perspectives, and contention points. In this paper, we focus on identifying the nature of interactions among user pairs. The central questions are: How does each pair of users interact with each other? Does the pair of users mostly agree or disagree? What is the lexicon that people often use to express agreement and disagreement? We present a topic model based approach to answer these questions. Since agreement and disagreement expressions are usually multiword phrases, we propose to employ a ranking method to identify highly relevant phrases prior to topic modeling. After modeling, we use the modeling results to classify the nature of interaction of each user pair. Our evaluation results using real-life discussion/debate posts demonstrate the effectiveness of the proposed techniques.
Abu-Jbara, A., Dasigi, P., Diab, M. and Dragomir Radev. 2012. Subgroup detection in ideological discussions. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2012). Agrawal, R., Rajagopalan, S., Srikant, R., and Xu. Y. 2003. Mining newsgroups using networks arising from social behavior. In Proceedings of the International Conference on World Wide Web (WWW-2003). Ahmed, A and Xing, E. 2010. Staying informed: supervised and semi-supervised multi-view topical analysis of ideological perspective. In Proceedings of the Empirical Methods in Natural Language Processing (EMNLP-2010). Anand, P., Walker, M., Abbott, R., Tree, J., Bowmani, R., and Minor, M. 201 1. Cats rule and dogs drool! : Classifying stance in online debate. In Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis. Bansal, M., Cardie, C., and Lee, L. 2008. The power of negative thinking: Exploiting label disagreement in the min-cut classification framework. In Proceedings of the International Conference on Computational Linguistics (Short Paper). Blei, D., Ng, A., and Jordan, M. 2003. Latent Dirichlet Allocation. Journal of Machine Learning Research. Blei, D. and Lafferty J. 2009. Visualizing topics with multi-word expressions. Tech. Report. arXiv:0907.1013v1 . Brody, S. and Elhadad, S. 2010. An Unsupervised Aspect-Sentiment Model for Online Reviews. In Proceedings of the Annual Conference of the North American Chapter of the ACL (NAACL-2010). Burfoot, C., Bird, S., and Baldwin, T. 2011. Collective Classification of Congressional Floor-Debate Transcripts. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2001). Chang, J., Boyd-Graber, J., Wang, C. Gerrish, S. Blei, D. 2009. Reading tea leaves: How humans interpret topic models. In Proceedings of the Neural Information Processing Systems (NIPS-2009). Chen, Z., Mukherjee, A., Liu, B., Hsu, M., Castellanos, M., Ghosh, R. 2013. Leveraging MultiDomain Prior Knowledge in Topic Models. In Proceedings of the International Joint Conference in Artificial Intelligence (IJCAI-2013). Choi, Y. and Cardie, C. 2010. Hierarchical sequential learning for extracting opinions and their attributes (Short Paper). In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2010). Du, L., Buntine, W. L., and Jin, H. 2010. Sequential Latent Dirichlet Allocation: Discover Underlying Topic Structures within a Document. In Proceedings of the IEEE International Conference on Data Mining (ICDM-2010). Erosheva, E., Fienberg, S. and Lafferty, J. 2004. Mixed membership models of scientific publications. In Proceedings of the National Academy of Sciences (PNAS-2004). Galley, M., McKeown, K., Hirschberg, J., and Shriberg, E. 2004. Identifying agreement and disagreement in conversational speech: Use of Bayesian networks to model pragmatic dependencies. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2004). Griffiths, T. and Steyvers, M. 2004. Finding scientific topics. In Proceedings of the National Academy of Sciences (PNAS-2004). Hansen, G. J., and Hyunjung, K. 201 1. Is the media biased against me? A meta-analysis of the hostile media effect research. Communication Research Reports, 28, 169-179. Hillard, D., Ostendorf, M., and Shriberg, E. 2003. Detection of agreement vs. disagreement in meetings: Training with unlabeled data. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT-2003). Hassan, A. and Radev, D. 2010. Identifying text polarity using random walks. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2010). Hofmann, T. 1999. Probabilistic latent semantic analysis. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI-1999). Hu, M. and Liu, B. 2004. Mining and summarizing customer reviews. In Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004). Jo, Y. and Oh, A. 201 1. Aspect and sentiment unification model for online review analysis. In Proceedings of the International Conference on Web Search and Data Mining (WSDM-201 1). Joachims, T. Making large-Scale SVM Learning Practical. 1999. Advances in Kernel Methods Support Vector Learning, B. Schölkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999. Lafferty, J. and Zhai, C. 2003. Probabilistic relevance models based on document and query generation. Language Modeling and Information Retrieval. Landis, J. R. and Koch, G. G. 1977. The measurement of observer agreement for categorical data. Biometrics. Lin, C. and He, Y. 2009. Joint sentiment/topic model for sentiment analysis. In Proceedings of the 680 International Conference on Knowledge Management (CIKM-2009). Lin, W. H., and Hauptmann, A. 2006. Are these documents written from different perspectives?: a test of different perspectives based on statistical distribution divergence. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2006). Liu, B. 2012. Sentiment Analysis and Opinion Mining. Morgan & Claypool Publisher, USA. McCallum, A., Wang, X., and Corrada-Emmanuel, A. 2007. Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email. Journal of Artificial Intelligence Research. Mei, Q., Ling, X., Wondra, M., Su, H., and Zhai, C. 2007. Topic sentiment mixture: modeling facets and opinions in weblogs. In Proceedings of the International Conference on World Wide Web (WWW-2007). Mimno, D. and McCallum, A. 2007. Expertise modeling for matching papers with reviewers. In Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2007). Mukherjee, A., Venkataraman, V., Liu, B., Meraz, S. 2013. Public Dialogue: Analysis of Tolerance in Online Discussions. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2013). Mukherjee, A. and Liu, B. 2012a. Mining Contentions from Discussions and Debates. Proceedings of SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2012). Mukherjee, A. and Liu, B. 2012b. Aspect Extraction through Semi-Supervised Modeling. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2012). Mukherjee, A. and Liu, B. 2012c. Analysis of Linguistic Style Accommodation in Online Debates. In Proceedings of the International Conference on Computational Linguistics (COLING-2012). Mukherjee, A. and Liu, B. 2012d. Modeling Review Comments. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-2012). Murakami A. and Raymond, R. 2010. Support or Oppose? Classifying Positions in Online Debates from Reply Activities and Opinion Expressions. In Proceedings of the International Conference on Computational Linguistics (Coling-2010). Pang, B. and Lee, L. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval. Popescu, A. and Etzioni, O. 2005. Extracting product features and opinions from reviews. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2005). Ramage, D., Hall, D., Nallapati, R, Manning, C. 2009. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2009). Rosen-Zvi, M., Griffiths, T., Steyvers, M., and Smith, P. 2004. The author-topic model for authors and documents. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI-2004). Sunstein, C. R. 2002. The law of group polarization. Journal of political philosophy. Somasundaran, S. and Wiebe, J. 2009. Recognizing stances in online debates. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing (ACL-IJCNLP-2009). Titov, I. and R. McDonald. 2008. Modeling online reviews with multi-grain topic models. In Proceedings of the International Conference on World Wide Web (WWW-2008). Thomas, M., Pang, B., and Lee, L. 2006. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In Proc. of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2006). Tomokiyo, T., and Hurst, M. 2003. A language model approach to keyphrase extraction. In Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment-Volume 18. Wallach, H. 2006. Topic modeling: Beyond bag of words. In Proceedings of the International Conference on Machine Learning (ICML-2006). Wang, X., McCallum, A., Wei, X. 2007. Topical Ngrams: Phrase and topic discovery, with an application to information retrieval. In Proceedings of the IEEE International Conference on Data Mining (ICDM-2007). Wiebe, J. 2000. Learning subjective adjectives from corpora. In Proc. of National Conference on AI (AAAI-2000). Yano, T., Cohen, W. and Smith, N. 2009. Predicting response to political blog posts with topic models. In Proceedings of the N. American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT-2009). Zhao, X., J. Jiang, J. He, Y. Song, P. Achananuparp, E.P. LiM, and X. Li. 201 1. Topical keyphrase extraction from twitter. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL-201 1). Zhao, X., Jiang, J., Yan, H., and Li, X. 2010. Jointly modeling aspects and opinions with a MaxEntLDA hybrid. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2010). 681