Transformers at SemEval-2022 Task 5: A Feature Extraction based Approach for Misogynous Meme Detection

no code implementations • SemEval (NAACL) 2022 • Shankar Mahadevan, Sean Benhur, Roshan Nayak, Malliga Subramanian, Kogilavani Shanmugavadivel, Kanchana Sivanraju, Bharathi Raja Chakravarthi

Social media is an idea created to make theworld smaller and more connected.

Hypers at ComMA@ICON: Modelling Aggressive, Gender Bias and Communal Bias Identification

1 code implementation • ICON 2021 • Sean Benhur, Roshan Nayak, Kanchana Sivanraju, Adeep Hande, Cn Subalalitha, Ruba Priyadharshini, Bharathi Raja Chakravarthi

Due to the exponential increasing reach of social media, it is essential to focus on its negative aspects as it can potentially divide society and incite people into violence.

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TamilEmo: Finegrained Emotion Detection Dataset for Tamil

no code implementations • 9 Feb 2022 • Charangan Vasantharajan, Sean Benhur, Prasanna Kumar Kumarasen, Rahul Ponnusamy, Sathiyaraj Thangasamy, Ruba Priyadharshini, Thenmozhi Durairaj, Kanchana Sivanraju, Anbukkarasi Sampath, Bharathi Raja Chakravarthi, John Phillip McCrae

Our MURIL-base model has achieved a 0. 60 macro average F1-score across our 3-class group dataset.

Emotion Recognition

Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification

1 code implementation • 31 Dec 2021 • Sean Benhur, Roshan Nayak, Kanchana Sivanraju, Adeep Hande, Subalalitha Chinnaudayar Navaneethakrishnan, Ruba Priyadharshini, Bharathi Raja Chakravarthi

Due to the exponentially increasing reach of social media, it is essential to focus on its negative aspects as it can potentially divide society and incite people into violence.

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Pretrained Transformers for Offensive Language Identification in Tanglish

1 code implementation • 6 Oct 2021 • Sean Benhur, Kanchana Sivanraju

Our approach utilizes pooling the last layers of pretrained transformer multilingual BERT for this task which helped us achieve rank nine on the leaderboard with a weighted average score of 0. 61 for the Tamil-English dataset in subtask B.

Language Identification Text Classification