Pulse: Mining Customer Opinions from Free Text

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.

[1]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[2]  Martin F. Porter,et al.  An algorithm for suffix stripping , 1997, Program.

[3]  Ted Dunning,et al.  Accurate Methods for the Statistics of Surprise and Coincidence , 1993, CL.

[4]  Marina Meila,et al.  An Experimental Comparison of Several Clustering and Initialization Methods , 1998, UAI.

[5]  Marc A. Smith,et al.  Visualization components for persistent conversations , 2001, CHI.

[6]  Joshua Goodman,et al.  A bit of progress in language modeling , 2001, Comput. Speech Lang..

[7]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[8]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[9]  Peter D. Turney.  Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews , 2002, ACL.

[10]  Michael L. Littman,et al.  Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus , 2002, ArXiv.

[11]  Bo Pang,et al.  A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.

[12]  Edoardo M. Airoldi,et al.  Sentiment Extraction from Unstructured Text using Tabu Search-Enhanced Markov Blanket , 2004 .

[13]  Sebastian Thrun,et al.  Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.

[14]  Michael Gamon,et al.  Automatic Identification of Sentiment Vocabulary: Exploiting Low Association with Known Sentiment Terms , 2005, ACL 2005.