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This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. We provide empirical evidence that SWSD is more feasible than full word sense disambiguation, and that it can be exploited to improve the performance of contextual subjectivity and sentiment analysis systems.
Akkaya et al. (Thu,) studied this question.
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