Fake News Detection Using Sentiment Analysis

Abstract

Social media is one of the most revolutionary inventions of the present times. With its own set of advantages and disadvantages it is extremely essential for each one of us. Today Fake News has become a major problem wreaking havoc all over the world. Therefore building an algorithm with the best possible accuracy will be a revelation and it will have a massive impact on the social issues which are prevalent as well as on the current political scenario. Social Media and online news articles serve as a major source of news and for data for people since it can be approached easily, has a subsidized costing and is readily available-just a click away. However, it does have several negative impacts too such as no check on the source or authenticity and validity of the views being endorsed. Hence, we have proposed a new solution for fake news detection which incorporates sentiment as an important feature to improve the accuracy. It also investigates the performance of proposed method using three different data sets. Results show that proposed solution performs well. Moreover, the comparison is also made with other methods under this study.

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