Subhankar Mishra

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2021

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NLP@NISER: Classification of COVID19 tweets containing symptoms
Deepak Kumar | Nalin Kumar | Subhankar Mishra
Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task

In this paper, we describe our approaches for task six of Social Media Mining for Health Applications (SMM4H) shared task in 2021. The task is to classify twitter tweets containing COVID-19 symptoms in three classes (self-reports, non-personal reports & literature/news mentions). We implemented BERT and XLNet for this text classification task. Best result was achieved by XLNet approach, which is F1 score 0.94, precision 0.9448 and recall 0.94448. This is slightly better than the average score, i.e. F1 score 0.93, precision 0.93235 and recall 0.93235.
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