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Withtheadventofsocialmedia,therehasbeenanextremely rapid increase in thecontent shared online. Consequently, the propagation of fake news and hostilemessages on social media platforms has also skyrocketed. In this paper, weaddress the problem of detecting hostile and fake content in the Devanagari(Hindi) script as a multi-class, multi-label problem. Using NLP techniques, webuild a model that makes use of an abusive language detector coupled withfeatures extracted via Hindi BERT and Hindi FastText models and metadata. Ourmodel achieves a 0.97 F1 score on coarse grain evaluation on Hostilitydetection task. Additionally, we built models to identify fake news related toCovid-19 in English tweets. We leverage entity information extracted from thetweets along with textual representations learned from word embeddings andachieve a 0.93 F1 score on the English fake news detection task.

Hostility Detection and Covid-19 Fake News Detection in Social Media