Battling Hateful Content in Indic Languages HASOC '21

Aditya Kadam; Anmol Goel; Jivitesh jain; Jushaan Singh Kalra; Mallika Subramanian; Manish Shrivastava; Manvith Reddy; Ponnurangam Kumaraguru; Prashant Kodali; T.H. Arjun

Battling Hateful Content in Indic Languages HASOC '21

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arxiv 2110.12780 v2 pith:UEPCA4CU submitted 2021-10-25 cs.CL

Aditya Kadam , Anmol Goel , Jivitesh Jain , Jushaan Singh Kalra , Mallika Subramanian , Manvith Reddy , Prashant Kodali , T.H. Arjun

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Manish Shrivastava Ponnurangam Kumaraguru

This is my paper · ORCID

classification cs.CL

keywords challengecontenthasochatefullanguagesmultilingualosmssubtasks

verification ladder T0 review T1 audit T2 compute T3 formal

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The extensive rise in consumption of online social media (OSMs) by a large number of people poses a critical problem of curbing the spread of hateful content on these platforms. With the growing usage of OSMs in multiple languages, the task of detecting and characterizing hate becomes more complex. The subtle variations of code-mixed texts along with switching scripts only add to the complexity. This paper presents a solution for the HASOC 2021 Multilingual Twitter Hate-Speech Detection challenge by team PreCog IIIT Hyderabad. We adopt a multilingual transformer based approach and describe our architecture for all 6 subtasks as part of the challenge. Out of the 6 teams that participated in all the subtasks, our submissions rank 3rd overall.

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