Paper: Improving the Impact of Subjectivity Word Sense Disambiguation on Contextual Opinion Analysis

ACL ID W11-0311
Title Improving the Impact of Subjectivity Word Sense Disambiguation on Contextual Opinion Analysis
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2011
Authors

Subjectivity word sense disambiguation (SWSD) is automatically determining which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. SWSD has been shown to improve the performance of contextual opinion analysis, but only on a small scale and using manually developed integration rules. In this paper, we scale up the integration of SWSD into contextual opinion analysis and still obtain improvements in performance, by successfully gathering data annotated by non-expert annotators. Further, by improving the method for integrating SWSD into con- textual opinion analysis, even greater benefits from SWSD are achieved than in previous work. We thus more firmly demonstrate the potential of SWSD to improve contextual opinion analysis.