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

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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Bibliographic Details
Main Authors: Shashi Shekhar, Hitendra Garg, Rohit Agrawal, Shivendra Shivani, Bhisham Sharma
Format: Article
Language:English
Published: Springer 2021-08-01
Series:Complex & Intelligent Systems
Subjects:
Hatred detection
Trolling
Social media
HLSTM
Embedding
Transliteration
Online Access:https://doi.org/10.1007/s40747-021-00487-7

Internet

https://doi.org/10.1007/s40747-021-00487-7

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