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Tackling the Infodemic: Analysis Using Transformer Based Models

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Combating Online Hostile Posts in Regional Languages during Emergency Situation (CONSTRAINT 2021)

Abstract

This paper presents how we tackled the COVID 19 Fake News Detection in English subtask in the SHARED TASK@ CONSTRAINT 2021 using RoBERTa. We perform extensive analysis to understand the pattern of the data distribution. To achieve an F1 score of 0.96, we incorporate external sources of misinformation and fine tune multiple state of the art pretrained deep learning models. In the end, we visualise the true and false positives predicted by our model as improvement in future work.

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Zutshi, A., Raj, A. (2021). Tackling the Infodemic: Analysis Using Transformer Based Models. In: Chakraborty, T., Shu, K., Bernard, H.R., Liu, H., Akhtar, M.S. (eds) Combating Online Hostile Posts in Regional Languages during Emergency Situation. CONSTRAINT 2021. Communications in Computer and Information Science, vol 1402. Springer, Cham. https://doi.org/10.1007/978-3-030-73696-5_10

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  • DOI: https://doi.org/10.1007/978-3-030-73696-5_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73695-8

  • Online ISBN: 978-3-030-73696-5

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