Hatred and trolling detection transliteration framework using hierarchical LSTM in code-mixed social media text

Abstract The paper describes the usage of self-learning Hierarchical LSTM technique for classifying hatred and trolling contents in social media code-mixed data. The Hierarchical LSTM-based learning is a novel learning architecture inspired from the neural learning models. The proposed HLSTM model i...

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Bibliografiska uppgifter

Huvudupphov:	Shashi Shekhar, Hitendra Garg, Rohit Agrawal, Shivendra Shivani, Bhisham Sharma
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Springer 2021-08-01
Serie:	Complex & Intelligent Systems
Ämnen:	Hatred detection Trolling Social media HLSTM Embedding Transliteration
Länkar:	https://doi.org/10.1007/s40747-021-00487-7
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