A Survey On Sentiment Analysis

Authors

  • M. Janaki  Assistant Professor, Department of Computer Science, Sacred Heart Girls First Grade College, Bengaluru, Karnataka, India

Keywords:

Sentiment Analysis, Polarity classification, Techniques, Applications, Challenges.

Abstract

Sentiment analysis is a technique to analyze people’s opinion on given topics such as political, social, and economical or review on product etc.The techniques for sentiment analysis include machine learning (supervised and unsupervised), and lexical-based approaches. The most important focus of the realm of Sentiment analysis lies find the emotions indicate within the texts. Sentiment analysis allows us to extract reviews and present the summary which could be beneficial for market research and product enhancement.It helps business and organization because it’s easy for them to know how people feel about their product or services so that they can make better decision or improve their services. For that purpose we have different sentiment analysis techniques like Naïve Bayes, Maximum Entropy, and Support Vector Machine which gives correctness of information or provides us accuracy. For sentiment we use machine learning because it train the computer to recognize the emoticon behind the sentence.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-10-12

Issue

Volume 4, Issue 7, September-October-2019

Section

Research Articles

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How to Cite

[1]
M. Janaki, " A Survey On Sentiment Analysis, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 7, pp.20-26, September-October-2019.