Sentiment Analysis

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Author(s): A. M. Abirami (Thiagarajar College of Engineering, India), A. Sheik Abdullah (Thiagarajar College of Engineering, India), A. Askarunisa (KLN College of Information Technology, India), S. Selvakumar (G. K. M. College of Engineering and Technology, India)and C. Mahalakshmi (Thiagarajar College of Engineering, India)
Copyright: 2017
Pages: 13
Source title: Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
Source Author(s)/Editor(s): Shrawan Kumar Trivedi (BML Munjal University, India), Shubhamoy Dey (Indian Institute of Management, Indore, India), Anil Kumar (BML Munjal University, India)and Tapan Kumar Panda (Jindal Global Business School, India)
DOI: 10.4018/978-1-5225-2031-3.ch009

Keywords: Business & Management / Business Information Systems / Business Intelligence / Business Science Reference

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Abstract

It requires sophisticated streaming of big data processing to process the billions of daily social conversations across millions of sources. Dataset needs information extraction from them and it requires contextual semantic sentiment modeling to capture the intelligence through the complexity of online social discussions. Sentiment analysis is one of the techniques to capture the intelligence from Social Networks based on the user generated content. There are more and more researches evolving about sentiment classification. Aspect extraction is the core task involved in aspect based sentiment analysis. The proposed modeling uses Latent Semantic Analysis technique for aspect extraction and evaluates senti-scores of various products under study.

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