Supriya Chanda


2020

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IRLab@IITBHU at WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets using BERT
Supriya Chanda | Eshita Nandy | Sukomal Pal
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)

This paper reports our submission to the shared Task 2: Identification of informative COVID-19 English tweets at W-NUT 2020. We attempted a few techniques, and we briefly explain here two models that showed promising results in tweet classification tasks: DistilBERT and FastText. DistilBERT achieves a F1 score of 0.7508 on the test set, which is the best of our submissions.

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IRlab@IITV at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media Using SVM
Anita Saroj | Supriya Chanda | Sukomal Pal
Proceedings of the Fourteenth Workshop on Semantic Evaluation

This paper describes the IRlab@IIT-BHU system for the OffensEval 2020. We take the SVM with TF-IDF features to identify and categorize hate speech and offensive language in social media for two languages. In subtask A, we used a linear SVM classifier to detect abusive content in tweets, achieving a macro F1 score of 0.779 and 0.718 for Arabic and Greek, respectively.