Domain Independent Joint Sentiment And Topic Detection UsingAFINN And Other Lexicons
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 4
Abstract
Abstract: Sentiment analysis and opinion mining field concentrates on automatically classifying sentiments of documents. But detecting mere sentiments does not provide one the sufficient knowledge concealed in the text.In this paper, we have evaluated joint sentiment and topic detection model (JST) to detect sentiment and topicsimultaneously from text. JST is evaluated for movie reviews and product reviews with the help of domainindependent prior information. AS no labeled data is required for training JST, it becomes highly portable toany domain. JST provides user more information regarding the text than mere sentiments.
Authors and Affiliations
Supriya Paul , Sachin deshmukh
Keywords
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