Detection of Online Fake News using N-Gram Analysis and Machine
Pages : 1042-1045
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Abstract
Counterfeit news is a marvel which is significantly affecting our public activity, specifically in the political world. Counterfeit news recognition is a rising exploration territory which is picking up intrigue yet included a few difficulties because of the constrained measure of assets accessible. Data exactness on Internet, particularly via webbased networking media, is an inexorably significant concern, however web-scale information hampers, capacity to distinguish, assess and address such information, or alleged “counterfeit news,” present in these stages. This strategy utilizes NLP Classification model to foresee whether a post on Twiter will be marked as REAL or FAKE. With this task we are attempting to get high precision and furthermore decrease an opportunity to distinguish the Fake News. Likewise we can utilize this venture to distinguish the different phony news.
Keywords- Online fake news ,Text classification , Online social network security ,Fake news detection by using NLP analysis