Colloquium
Subjectivity and Sentiment Analysis
Jan Wiebe
University of Pittsburgh
Host: Ellen Riloff
Friday, June 23, 2006
3147 MEB
Lecture 3:00 p.m.
The goals of subjectivity analysis are to extract opinions, sentiments, and emotions expressed in natural language discourse and to recognize their components and properties. This is currently a very active area of research in natural language processing (NLP), with the potential to develop tools supporting information analysts in governmental, commercial, and political domains who want to automatically track attitudes and feelings in the news and on-line forums. How do people feel about the latest camera phone? Is there a change in the support for the new Medicare bill? A system able to automatically identify and extract opinions and sentiments from text would be an enormous help to someone sifting through the vast amounts of news and web data, trying to answer these kinds of questions. In this talk, I will first describe a corpus annotated with rich information about opinions and sentiments, and then present recent experiments using that data to develop and evaluate automatic systems. In particular, I will describe experiments in recognizing the "contextual polarity" of expressions, i.e., whether a phrase is being used to express a positive or negative sentiment, considering the context in which it appears. I will also describe experiments exploring interactions between subjectivity and word sense, showing that subjectivity is a property that can be associated with word meanings and that subjectivity classification can be beneficial for word sense disambiguation.
Biography
Jan Wiebe is a professor of computer science and Director of the Intelligent Systems Program at the University of Pittsburgh. Previously, she was a faculty member at New Mexico State University and, before that, a post-doctoral fellow at the University of Toronto. She has worked in discourse processing, pragmatics, word-sense disambiguation, and probabilistic classification in NLP. Her most recent work investigates automatically recognizing opinionated and evaluative language to support NLP applications such as question answering, information extraction, text categorization, and summarization. Her previous and current professional roles include NAACL Program Committee Chair, NAACL Executive Board member, Computational Linguistics and Language Resources and Evaluation Editorial Board member, AAAI Workshop Co-Chair, ACM Special Interest Group on Artificial Intelligence (SIGART) Vice-Chair, and ACM-SIGART/AAAI Doctoral Consortium Chair.
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