VIABLE MODERN APPROACHES FOR SENTIMENT ANALYSIS: A SURVEY

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Published: Aug 28, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i7.4095
Keywords:
Sentiment analysis, machine learning, lexicon analysis, supervised learning, text analysis.

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Srinvas A
HOD & Director, Department of Computer Science, Surana College,#16, South End Circle, Basavangudi, Bangalore - 560004, Karnataka, India.
Hanumanthappa M
Professor, Dept. of Computer Science & Applications, Bangalore University, Jnanabharathi Campus Bangalore, India

Abstract

Sentiment analysis is a process of extracting, identifying and categorizing a writer’s emotion, expressed in the form of text, by implying a computational method. This paper presents a study of various modern approaches for sentiment analysis along with the hurdles and possible solutions present in these approaches. Further, the study is concentrated on two main categories, machine learning and lexicon analysis, for sentiment analysis. Even though, the various methods falling under these two main approaches are elaborated and illustrated, the supervised learning method of machine learning is more concentrated in the article. This paper also describes a generalized sentiment analysis method that can be incorporated with any of the existing analytical algorithms for sentiment analysis as well as any mundane text analysis.

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Vol. 8 No. 7 (2017): July-August 2017
Section
Articles

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Author Biographies

Srinvas A, HOD & Director, Department of Computer Science, Surana College,#16, South End Circle, Basavangudi, Bangalore - 560004, Karnataka, India.

HOD & Director, Department of Computer Science

Hanumanthappa M, Professor, Dept. of Computer Science & Applications, Bangalore University, Jnanabharathi Campus Bangalore, India

Professor, Dept. of Computer Science & Applications

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