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WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive language identification in code-switched youtube comments

  • Tharindu Ranasinghe
  • , Sarthak Gupte
  • , Marcos Zampieri
  • , Ifeoma Nwogu
  • University of Wolverhampton
  • Rochester Institute of Technology

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

This paper describes the WLV-RIT entry to the Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC) shared task 2020. The HASOC 2020 organizers provided participants with annotated datasets containing social media posts of code-mixed in Dravidian languages (Malayalam-English and Tamil-English). We participated in task 1: Offensive comment identification in Code-mixed Malayalam Youtube comments. In our methodology, we take advantage of available English data by applying cross-lingual contextual word embeddings and transfer learning to make predictions to Malayalam data. We further improve the results using various fine tuning strategies. Our system achieved 0.89 weighted average F1 score for the test set and it ranked 5 place out of 12 participants.

Original languageEnglish
Pages (from-to)417-426
Number of pages10
JournalCEUR Workshop Proceedings
Volume2826
StatePublished - 2020
EventWorking Notes of FIRE - 12th Forum for Information Retrieval Evaluation, FIRE-WN 2020 - Hyderabad, India
Duration: Dec 16 2020Dec 20 2020

Keywords

  • Code-switching
  • Hate speech
  • Offensive language identification
  • Text classification

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