Representing and Resolving Negation for Sentiment Analysis
Published 1 December 2012
Emanuele Lapponi, Jonathon Read, Lilja Øvrelid
Citations50
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TL;DR
This work presents a state-of-the-art system for negation resolution that is interoperable across these schemes and demonstrates that the choice of representation can have a significant impact on downstream processing.
Abstract
Proper treatment of negation is an important characteristic of methods for sentiment analysis. However, while there is a growing body of research on the automatic resolution of negation, it is not yet clear as to how negation is best represented for different applications. To begin to address this issue, we review representation alternatives and present a state-of-the-art system for negation resolution that is interoperable across these schemes. By employing different configurations of this system as a component in a test bed for lexically-based sentiment classification, we demonstrate that the choice of representation can have a significant impact on downstream processing.
Keywords
Computer Science
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