Naman Jhunjhunwala


2021

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NARNIA at NLP4IF-2021: Identification of Misinformation in COVID-19 Tweets Using BERTweet
Ankit Kumar | Naman Jhunjhunwala | Raksha Agarwal | Niladri Chatterjee
Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda

The spread of COVID-19 has been accompanied with widespread misinformation on social media. In particular, Twitterverse has seen a huge increase in dissemination of distorted facts and figures. The present work aims at identifying tweets regarding COVID-19 which contains harmful and false information. We have experimented with a number of Deep Learning-based models, including different word embeddings, such as Glove, ELMo, among others. BERTweet model achieved the best overall F1-score of 0.881 and secured the third rank on the above task.