Twitter Sentiment Analysis Using a Modified Naïve Bayes Algorithm

Masrani, Manav and Poornalatha, G (2017) Twitter Sentiment Analysis Using a Modified Naïve Bayes Algorithm. Advances in Intelligent Systems and Computing, 655 (1). pp. 171-181. ISSN 2194-5357

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Abstract

Microblogging has emerged as a popular platform and a powerful commu-nication tool among people nowadays. A clear majority of people share their opinions about various aspects of their lives online every day. Thus, microblogging websites offer rich sources of data in order to perform sentiment analysis and opinion mining. Because microblogging has emerged relatively recently there are only some research works which are devoted to this field. In this paper, the focus is on performing the task of sentiment analysis using Twitter which is one of the most popular microblog-ging platforms. Twitter is a very popular microblogging site where its users write sta-tus messages called tweets to express themselves. These status updates mostly express their opinions about various topics. The objective of this paper is to build a system that can classify these Twitter status updates as positive, negative, or neutral with re-spect to any query term thereby giving an idea about the overall sentiment of the peo-ple towards that topic. This type of sentiment analysis is useful for advertisers, con-sumers researching a service or product, companies, governments, marketers, or any organization who are researching public opinion

Item Type: Article
Uncontrolled Keywords: twitter, data mining, sentiment analysis.
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 27 Sep 2017 04:56
Last Modified: 27 Sep 2017 04:56
URI: http://eprints.manipal.edu/id/eprint/149745

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