A Review: Sentiment Analysis and Opinion Mining

6 Pages Posted: 19 May 2020 Last revised: 7 Jul 2020

See all articles by Apoorva Arya

Apoorva Arya

National Institute of Technology, Kurukshetra

Vishal Shukla

National Institute of Technology, Kurukshetra

Arvind Negi

National Institute of Technology, Kurukshetra

Kapil Gupta

National Institute of Technology, Kurukshetra

Date Written: May 16, 2020

Abstract

The rapid growth in social media along its users has given rise to the need of Sentiment analysis also called Opinion mining or emotion abstraction, whose goal is to extract, determine, analyze and present the sentiments of the user and drawing a conclusion about the overall information they contain in less cost and efficient time complexity. Opinions or sentiments in the form of a forum, comment, review sites, blogs, etc. can be about the product, people, services, events, politics, etc. The aim is to calculate the polarity of the data and classify it as positive, negative, or neutral. This paper presents a review of techniques and methods in sentiment analysis with their challenges.

Keywords: Bayesian Algorithm, Feature Extraction, Machine learning, Opinion, Sentiment Analysis, Sentiment Classification, SVM, Twitter

Suggested Citation

Arya, Apoorva and Shukla, Vishal and Negi, Arvind and Gupta, Kapil, A Review: Sentiment Analysis and Opinion Mining (May 16, 2020). Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020, Available at SSRN: https://ssrn.com/abstract=3602548 or http://dx.doi.org/10.2139/ssrn.3602548

Apoorva Arya (Contact Author)

National Institute of Technology, Kurukshetra ( email )

Vishal Shukla

National Institute of Technology, Kurukshetra ( email )

Arvind Negi

National Institute of Technology, Kurukshetra ( email )

Kapil Gupta

National Institute of Technology, Kurukshetra ( email )

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