T. Y.S.S. Santosh
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.
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Index Terms
- Hate Speech Detection in Hindi-English Code-Mixed Social Media Text
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