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20212024
most citedHate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection

14 citations · 22 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20241 cited

CrowdCounter: A benchmark type-specific multi-target counterspeech dataset

Punyajoy Saha, Abhilash Datta, Abhik Jana +1

Counterspeech presents a viable alternative to banning or suspending users for hate speech while upholding freedom of expression. However, writing effective counterspeech is challe…

cs.CL20226 cited

Hate Speech and Offensive Language Detection in Bengali

Mithun Das, Somnath Banerjee, Punyajoy Saha +1

Social media often serves as a breeding ground for various hateful and offensive content. Identifying such content on social media is crucial due to its impact on the race, gender,…

cs.CL2022

HateCheckHIn: Evaluating Hindi Hate Speech Detection Models

Mithun Das, Punyajoy Saha, Binny Mathew +1

Due to the sheer volume of online hate, the AI and NLP communities have started building models to detect such hateful content. Recently, multilingual hate is a major emerging chal…

cs.SI20211 cited

You too Brutus! Trapping Hateful Users in Social Media: Challenges, Solutions & Insights

Mithun Das, Punyajoy Saha, Ritam Dutt +3

Hate speech is regarded as one of the crucial issues plaguing the online social media. The current literature on hate speech detection leverages primarily the textual content to fi…

cs.CL202114 cited

Hate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection

Debjoy Saha, Naman Paharia, Debajit Chakraborty +2

Social media often acts as breeding grounds for different forms of offensive content. For low resource languages like Tamil, the situation is more complex due to the poor performan…