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A Comparative Study of Different State-of-the-Art Hate Speech Detection Methods for Hindi-English Code-Mixed Data

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
Hate speech detection in social media communication has become one of the primary concerns to avoid conflicts and curb undesired activities. In an environment where multilingual speakers switch among multiple languages, hate speech detection becomes a challenging task using methods that are designed for monolingual corpora. In our work, we attempt to analyze, detect and provide a comparative study of hate speech in a code-mixed social media text. We also provide a Hindi-English code-mixed data set consisting of Facebook and Twitter posts and comments. Our experiments show that deep learning models trained on this code-mixed corpus perform better.
Conference Name: 
TRAC-2: The Second Workshop on Trolling, Aggression & Cyberbullying, co-located with 12th Edition of Language Resources and Evaluation Conference
Proceedings: 
TRAC-2: The Second Workshop on Trolling, Aggression & Cyberbullying, co-located with 12th Edition of Language Resources and Evaluation Conference
Digital Object Identifer (DOI): 
10.
Publication Date: 
11/05/2020
Conference Location: 
France
Research Group: 
Institution: 
National University of Ireland, Galway (NUIG)
Open access repository: 
Yes