Fake News Detection Using Machine Learning
Keywords:
Machine Learning, Naïve Bayes Classifier, Web Scrapping, Clustering.Abstract
Information preciseness on Internet, especially on social media, is an increasingly important concern, but web-scale data hampers, ability to identify, evaluate and correct such data, or so called “fake news,” present in these platforms. 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. Received results suggest, that fake news detection problem can be addressed with machine learning methods.
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