Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/45389
Title: Role of sentiment classification in sentiment analysis: a survey
Authors: Kumar, Pavan M R
Prabhu, J
Keywords: Accuracy;Binary Classification;Dataset;Lexicon;Machine learning;Sentiment analysis
Issue Date: Sep-2018
Publisher: NISCAIR-CSIR, India
Abstract: Through a survey of literature, the role of sentiment classification in sentiment analysis has been reviewed. The review identifies the research challenges involved in tackling sentiment classification. A total of 68 articles during 2015 – 2017 have been reviewed on six dimensions viz., sentiment classification, feature extraction, cross-lingual sentiment classification, cross-domain sentiment classification, lexica and corpora creation and multi-label sentiment classification. This study discusses the prominence and effects of sentiment classification in sentiment evaluation and a lot of further research needs to be done for productive results.
Page(s): 196-209
URI: http://nopr.niscair.res.in/handle/123456789/45389
ISSN: 0975-2404 (Online); 0972-5423 (Print)
Appears in Collections:ALIS Vol.65(3) [September 2018]

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