Paper: Sentiment Relevance

ACL ID P13-1094
Title Sentiment Relevance
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013

A number of different notions, including subjectivity, have been proposed for dis- tinguishing parts of documents that con- vey sentiment from those that do not. We propose a new concept, sentiment rele- vance, to make this distinction and argue that it better reflects the requirements of sentiment analysis systems. We demon- strate experimentally that sentiment rele- vance and subjectivity are related, but dif- ferent. Since no large amount of labeled training data for our new notion of sen- timent relevance is available, we investi- gate two semi-supervised methods for cre- ating sentiment relevance classifiers: a dis- tant supervision approach that leverages structured information about the domain of the reviews; and transfer learning on feature representations based on lexical taxonomi...