Examining the role of linguistic knowledge sources in the automatic identification and classification of reviews
Published 1 January 2006Open access
Vincent Ng, Sajib Dasgupta, S. M. Niaz Arifin
Citations251
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TL;DR
It is demonstrated that review identification can be performed with high accuracy using only unigrams as features, and the role of four types of simple linguistic knowledge sources in a polarity classification system is examined.
Abstract
This paper examines two problems in document-level sentiment analysis: (1) determining whether a given document is a review or not, and (2) classifying the polarity of a review as positive or negative. We first demonstrate that review identification can be performed with high accuracy using only unigrams as features. We then examine the role of four types of simple linguistic knowledge sources in a polarity classification system.
Keywords
Computer Science
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