Fake News Detection on Social Media using K-Nearest Neighbor Classifier

Consumption of news from social media is gradually increasing because of it's easy to access, cheap and more attractive and it's capable to spread the “fake news”. The widespread of fake news has latent adverse impressions on people and culture. Some people spread wrong information on social media to get the attention or financial and political gain. We need to be smarter at the recognition of fake or real news. The unique feature of detecting fake news on social media that make current detection algorithms ine □ ective or not appropriate. Thereafter is essential to consider secondary information. Secondary information may include social activities of user on social media. So, in this research work we are presenting a simple approach for detecting fake news on social media with the help of K-Nearest Neighbor classifier. We achieved a classification accuracy of this model approximate 79% tested against Facebook news posts dataset.