FAKE NEWS DETECTION USING MACHINE LEARNING

FAKE NEWS DETECTION USING MACHINE LEARNING
Author(s):
Anju. G, Aishwarya Lekshmi.A.C
Keywords:

Abstract
In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects on the offline society already. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance. In this paper, we propose a method for "fake news" detection and ways to apply it on Facebook, one of the most popular online social media platforms. This method uses Naive Bayes classification model to predict whether a post on Facebook will be labeled as real or fake. The results may be improved by applying several techniques that are discussed in the paper.
Article Details
Unique Paper ID: 163051 Publication Volume & Issue: Volume 0, Issue no Page(s): 240 - 245
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