IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Comparative Study of Different Classification Techniques for Sentiment Analysis

A Comparative Study of Different Classification Techniques for Sentiment Analysis
View Sample PDF
Author(s): Soumadip Ghosh (Academy of Technology, Kolkata, India), Arnab Hazra (Academy of Technology, Kolkata, India)and Abhishek Raj (Academy of Technology, Kolkata, India)
Copyright: 2020
Volume: 11
Issue: 1
Pages: 9
Source title: International Journal of Synthetic Emotions (IJSE)
DOI: 10.4018/IJSE.20200101.oa

Purchase

View A Comparative Study of Different Classification Techniques for Sentiment Analysis on the publisher's website for pricing and purchasing information.

Abstract

Sentiment analysis denotes the analysis of emotions and opinions from text. The authors also refer to sentiment analysis as opinion mining. It finds and justifies the sentiment of the person with respect to a given source of content. Social media contain vast amounts of the sentiment data in the form of product reviews, tweets, blogs, and updates on the statuses, posts, etc. Sentiment analysis of this largely generated data is very useful to express the opinion of the mass in terms of product reviews. This work is proposing a highly accurate model of sentiment analysis for reviews of products, movies, and restaurants from Amazon, IMDB, and Yelp, respectively. With the help of classifiers such as logistic regression, support vector machine, and decision tree, the authors can classify these reviews as positive or negative with higher accuracy values.

Related Content

Adel Alti. © 2020. 10 pages.
Rana Seif Fathalla, Wafa Saad Alshehri. © 2020. 16 pages.
Sandip Palit, Soumadip Ghosh. © 2020. 9 pages.
Amiya Bhusan Bagjadab, Sushree Bibhuprada B. Priyadarshini. © 2020. 13 pages.
Soumadip Ghosh, Arnab Hazra, Abhishek Raj. © 2020. 9 pages.
Sushree Bibhuprada B. Priyadarshini. © 2020. 19 pages.
Rana Fathalla. © 2020. 18 pages.
Body Bottom