Linguistic features based model or fake news identification.

The easy accessibility of social media to everyone generates serious problems. Misleading news affect the mental health of peoples. False news can easily be created and propagated using online platform by using an Un-anonymous account. it is required to control the spread of fake news on social media. In this paper we used several linguistic features for fake news classification along with machine learning model. The linguistic features used are number of characters, number of words, noun-count, and number of articles. This study provides the heuristic solution by using both the news text and Linguistic features of text for better news classification. LIAR dataset is used for experiments. Our method outperforms the existing method. [ABSTRACT FROM AUTHOR]