Paper: Discovering the Discriminative Views: Measuring Term Weights for Sentiment Analysis

ACL ID P09-1029
Title Discovering the Discriminative Views: Measuring Term Weights for Sentiment Analysis
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper describes an approach to uti- lizing term weights for sentiment analysis tasks and shows how various term weight- ing schemes improve the performance of sentiment analysis systems. Previously, sentiment analysis was mostly studied un- der data-driven and lexicon-based frame- works. Such work generally exploits tex- tual features for fact-based analysis tasks or lexical indicators from a sentiment lexi- con. We propose to model term weighting into a sentiment analysis system utilizing collection statistics, contextual and topic- related characteristics as well as opinion- related properties. Experiments carried out on various datasets show that our approach effectively improves previous methods.