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A Survey on Sentiment Analysis Techniques for Twitter

A Survey on Sentiment Analysis Techniques for Twitter
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Author(s): Surabhi Verma (National Institute of Technology, Kurukshetra, India) and Ankit Kumar Jain (National Institute of Technology, Kurukshetra, India)
Copyright: 2022
Pages: 34
Source title: Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India), Dragan Peraković (University of Zagreb, Croatia), Ahmed A. Abd El-Latif (Menoufia University, Egypt) and Deepak Gupta (LoginRadius Inc., Canada)
DOI: 10.4018/978-1-7998-8413-2.ch003

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Abstract

People regularly use social media to express their opinions about a wide variety of topics, goods, and services which make it rich in text mining and sentiment analysis. Sentiment analysis is a form of text analysis determining polarity (positive, negative, or neutral) in text, document, paragraph, or clause. This chapter offers an overview of the subject by examining the proposed algorithms for sentiment analysis on Twitter and briefly explaining them. In addition, the authors also address fields related to monitoring sentiments over time, regional view of views, neutral tweet analysis, sarcasm detection, and various other tasks in this area that have drawn the researchers ' attention to this subject nearby. Within this chapter, all the services used are briefly summarized. The key contribution of this survey is the taxonomy based on the methods suggested and the debate on the theme's recent research developments and related fields.

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