Sentiment Analysis and Sarcasm Detection (Using Emoticons)

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Author(s): Vibhu Dagar (Vellore Institute of Technology, Vellore, India), Amber Verma (Vellore Institute of Technology, Vellore, India)and Govardhan K. (Vellore Institute of Technology, Vellore, India)
Copyright: 2022
Pages: 11
Source title: Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch085

Keywords: Data Analysis and Statistics / Data Mining / Engineering Science Reference / Library & Information Science

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Abstract

Sentiment analysis is contextual mining of text which identifies and extracts subjective information in source material and helps a business to understand the social sentiment of their brand, product, or service while monitoring online conversations. However, analysis of social media streams is usually restricted to just basic sentiment analysis and count-based metrics. This is akin to just scratching the surface and missing out on those high value insights that are waiting to be discovered. Twitter is an online person-to-person communication administration where overall clients distribute their suppositions on an assortment of themes, talk about current issues, grumble, and express positive or on the other hand negative notions for items they use in life. Hence, Twitter is a rich source of information for supposition mining and estimation investigation.

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Sentiment Analysis and Sarcasm Detection (Using Emoticons)

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