Abstract
We present a prototype system, code-named Pulse, for mining topics and sentiment orientation jointly from free text customer feedback. We describe the application of the prototype system to a database of car reviews. Pulse enables the exploration of large quantities of customer free text. The user can examine customer opinion “at a glance” or explore the data at a finer level of detail. We describe a simple but effective technique for clustering sentences, the application of a bootstrapping approach to sentiment classification, and a novel user-interface.
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References
Turney, P.D.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. Proceedings of ACL 2002, 417–424 (2002)
Turney, P.D., Littman, M.L.: Unsupervised learning of semantic orientation from a hundred-billion-word corpus. Technical Report ERC-1094 (NRC 44929), National Research Council of Canada (2002)
Microsoft_Corporation: Msn autos (2005), http://autos.msn.com/default.aspx
Cohen, J.: A coefficient of agreement for nominal scales. Educational and Psychological measurements 20, 37–46 (1960)
Smith, M.A., Fiore, A.T.: Visualization components for persistent conversations. In: CHI 2001: Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 136–143. ACM Press, New York (2001)
Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. The MIT Press, Cambridge (1999)
Meila, M., Heckerman, D.: An experimental comparison of several clustering and initialization methods. Technical report, Microsoft Research (1998)
Goodman, J.: A bit of progress in language modeling. Technical report, Microsoft Research (2000)
Porter, M.: An algorithm for suffix stripping. Program 14, 130–137 (1980)
Dunning, T.: Accurate methods for the statistics of surprise and coincidence. Computational Linguistics 19, 61–74 (1993)
Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of EMNLP 2002, pp. 79–86 (2002)
Pang, B., Lee, L.: A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of ACL 2004, pp. 217–278 (2004)
Bai, X., Padman, R., Airoldi, E.: Sentiment extraction from unstructured text using tabu search enhanced markov blanket. In: Proceedings of the International Workshop on Mining for and from the Semantic Web, pp. 24–35 (2004)
Nigam, K., McCallum, A., Thrun, S., Mitchell, T.: Text classification from labeled and unlabeled documents using em. Machine Learning 39(2/3), 103–134 (2000)
Gamon, M., Aue, A.: Automatic identification of sentiment vocabulary: exploiting low association with known sentiment terms. In: Proceedings of the ACL 2005 Workshop on Feature Engineering for Machine Learning in NLP (2005) ACL (to appear)
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Gamon, M., Aue, A., Corston-Oliver, S., Ringger, E. (2005). Pulse: Mining Customer Opinions from Free Text. In: Famili, A.F., Kok, J.N., Peña, J.M., Siebes, A., Feelders, A. (eds) Advances in Intelligent Data Analysis VI. IDA 2005. Lecture Notes in Computer Science, vol 3646. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552253_12
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DOI: https://doi.org/10.1007/11552253_12
Publisher Name: Springer, Berlin, Heidelberg
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