JOURNAL ARTICLE

Hate Speech Detection in Hindi-English Code-Mixed Social Media Text

Abstract

With the increase in user generated content, particularly on social media networks, the amount of hate speech is also steadily increasing. So, there is a need to automatically detect such hateful content and curb the wrongful activities. While relevant research has been done independently on code-mixed social media texts and hate speech detection, this paper deals with the task of identification of hate speech from code-mixed social media text. We perform experiments with available code-mixed dataset for hate speech detection using two architectures namely sub-word level LSTM model and Hierarchical LSTM model with attention based on phonemic sub-words.

Keywords:
Computer science Social media Hindi Voice activity detection Natural language processing Code (set theory) Speech recognition Task (project management) Word (group theory) Artificial intelligence Language identification Identification (biology) Speech processing Linguistics World Wide Web Natural language

Metrics

107
Cited By
9.99
FWCI (Field Weighted Citation Impact)
21
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hate Speech and Cyberbullying Detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Internet Traffic Analysis and Secure E-voting
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

© 2026 ScienceGate Book Chapters — All rights reserved.