Hate Speech Detection on Vietnamese Social Media Text using the Bi-GRU-LSTM-CNN Model
Published in
arXiv.org(2019)External Links:
TL
TL;DR
A deep learning method based on the Bi-GRU-LSTM-CNN classifier is implemented into the VLSP shared task 2019: Hate Speech Detection on Social Networks with the corpus which contains 20,345 human-labeled comments/posts for training and 5,086 for public-testing.
Abstract
In recent years, Hate Speech Detection has become one of the interesting fields in natural language processing or computational linguistics. In this paper, we present the description of our system to solve this problem at the VLSP shared task 2019: Hate Speech Detection on Social Networks with the corpus which contains 20,345 human-labeled comments/posts for training and 5,086 for public-testing. We implement a deep learning method based on the Bi-GRU-LSTM-CNN classifier into this task. Our result in this task is 70.576\% of F1-score, ranking the 5th of performance on public-test set.
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SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
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Understanding Convolutional Neural Networks for Text Classification
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Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network
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Hate Speech Detection: A Solved Problem? The Challenging Case of Long Tail on Twitter
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