Sentiment and subjectivity analysis
From Language and Information Technologies
There has been a great deal of research in Natural Language Processing on automatically extracting facts and topics. But full-fledged knowledge discovery from text will require not only facts, but also sentiments, affect, and opinions (subjectivity). The goal of this research project is to develop accurate methods for the construction of resources and automatic methods for affect and sentiment analysis in multiple languages.
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People
- Rada Mihalcea (faculty)
- Carmen Banea (Ph.D. student)
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Publications
- Rada Mihalcea, Carmen Banea and Jan Wiebe, Learning Multilingual Subjective Language via Cross-Lingual Projections, In Proceedings of the Association for Computational Linguistics (ACL 2007), Prague, June 2007. |pdf|
- Hugo Liu and Rada Mihalcea, Of Men, Women, and Computers: Data-Driven Gender Modeling for Improved User Interfaces, In Proceedings of the International Conference on Weblogs and Social Media (ICWSM), Boulder, Colorado, March 2007. |pdf|
- Carlo Strapparava and Rada Mihalcea, SemEval-2007 Task 14: Affective Text, In Proceedings of the 4th International Workshop on the Semantic Evaluations (SemEval 2007), Prague, Czech Republic, June 2007. |pdf|
- Jan Wiebe and Rada Mihalcea, Word Sense And Subjectivity, In Proceedings of the Conference on Computational Linguistics / Association for Computational Linguistics (COLING/ACL-06), Sydney, Australia, July 2006. |pdf||ps|
- Rada Mihalcea and Hugo Liu, A corpus-based approach to finding happiness, In the AAAI Spring Symposium on Computational Approaches to Weblogs, March 2006. |pdf||ps|