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Hate Speech Detection on Vietnamese Social Media Text using the Bidirectional-LSTM Model
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In this paper, we describe our system which participates in the shared task of Hate Speech Detection on Social Networks of VLSP 2019 evaluation campaign. We are provided with the pre-labeled dataset and an unlabeled dataset for social media comments or posts. Our mission is to pre-process and build machine learning models to classify comments/posts. In this report, we use Bidirectional Long Short-Term Memory to build the model that can predict labels for social media text according to Clean, Offensive, Hate. With this system, we achieve comparative results with 71.43% on the public standard test set of VLSP 2019.
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A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages
A survey cataloging datasets, features, and machine-learning methods for automatic hate speech detection in low-resource languages, organized by world region, with an overview of open challenges.
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