Polarity Consistency Checking for Sentiment Dictionaries


Polarity classification of words is important for applications such as Opinion Mining and Sentiment Analysis. A number of sentiment word/sense dictionaries ave been manually or (semi)automatically constructed. The dictionaries have substantial inaccuracies. Besides obvious instances, where the same word appears with different polarities in different dictionaries, the dictionaries exhibit complex cases, which cannot be detected by mere manual inspection. We introduce the concept of polarity consistency of words/senses in sentiment dictionaries in this paper. We show that the consistency problem is NP-complete. We reduce the polarity consistency problem to the satisfiability problem and utilize a fast SAT solver to detect inconsistencies in a sentiment dictionary. We perform experiments on four sentiment dictionaries and WordNet.


polarity, opinion mining, word/sense dictionaries, polarity consistency, NP-complete, SAT solver, WordNet

Date of this Version



Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, pages 997–1005,
Jeju, Republic of Korea, 8-14 July 2012.
c 2012 Association for Computational Linguistics