Paper: Biographies Bollywood Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification

ACL ID P07-1056
Title Biographies Bollywood Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

Automatic sentiment classification has been extensively studied and applied in recent years. However, sentiment is expressed dif- ferently in different domains, and annotating corporaforeverypossibledomainofinterest is impractical. We investigate domain adap- tation for sentiment classifiers, focusing on online reviews for different types of prod- ucts. First, we extend to sentiment classifi- cation the recently-proposed structural cor- respondence learning (SCL) algorithm, re- ducing the relative error due to adaptation between domains by an average of 30% over the original SCL algorithm and 46% over a supervised baseline. Second, we identify a measure of domain similarity that corre- lates well with the potential for adaptation of a classifier from one domain to another. This measure cou...