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Fake News Polarization for Sentiment Analysis
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Author(s): Chirag Visani (Marwadi University, India), Vishal Sorathiya (Marwadi University, India)and Sunil Lavadiya (Marwadi University, India)
Copyright: 2022
Pages: 9
Source title:
Impact and Role of Digital Technologies in Adolescent Lives
Source Author(s)/Editor(s): Shaveta Malik (Terna Engineering College, India), Rohit Bansal (Department of Management Studies, Vaish College of Engineering, Rohtak, India)and Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-7998-8318-0.ch019
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Abstract
The popularity of the internet has increased the use of e-commerce websites and news channels. Fake news has been around for many years, and with the arrival of social media and modern-day news at its peak, easy access to e-platform and exponential growth of the knowledge available on social media networks has made it intricate to differentiate between right and wrong information, which has caused large effects on the offline society already. A crucial goal in improving the trustworthiness of data in online social networks is to spot fake news so the detection of spam news becomes important. For sentiment mining, the authors specialise in leveraging Facebook, Twitter, and Whatsapp, the most prominent microblogging platforms. They illustrate how to assemble a corpus automatically for sentiment analysis and opinion mining. They create a sentiment classifier using the corpus that can classify between fake, real, and neutral opinions in a document.
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