Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning Models

TL;DR

This paper advances hate speech detection in English-Hindi code-mixed tweets by comparing deep learning models with domain-specific embeddings, leading to improved detection performance.

Contribution

It introduces a comparative analysis of deep learning models with domain-specific embeddings for hate speech detection in code-mixed tweets, enhancing existing methods.

Findings

Domain-specific embeddings improve representation of target groups.

Enhanced F-score achieved with deep learning models and domain-specific embeddings.

Benchmark dataset used for evaluation.

Abstract

This paper reports an increment to the state-of-the-art in hate speech detection for English-Hindi code-mixed tweets. We compare three typical deep learning models using domain-specific embeddings. On experimenting with a benchmark dataset of English-Hindi code-mixed tweets, we observe that using domain-specific embeddings results in an improved representation of target groups, and an improved F-score.