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2012 IEEE 12th International Conference on Data Mining Workshops
Representing and Resolving Negation for Sentiment Analysis
Brussels, Belgium Belgium
December 10-December 10
ISBN: 978-1-4673-5164-5
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.
Index Terms:
Syntactics,Motion pictures,Feature extraction,Labeling,Gold,Communities,Context
Emanuele Lapponi, Jonathon Read, Lilja Ovrelid, "Representing and Resolving Negation for Sentiment Analysis," icdmw, pp.687-692, 2012 IEEE 12th International Conference on Data Mining Workshops, 2012
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