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2020 | OriginalPaper | Buchkapitel

Word Graph Network: Understanding Obscure Sentences on Social Media for Violation Comment Detection

verfasst von : Dan Ma, Haidong Liu, Dawei Song

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

Violation comment detection aims to recognize the texts that may violate the governing laws/regulations and cause adverse effect on social media. To avoid being intercepted, violation comments always informal and incomplete in an obscure expression poses challenge to violation detection algorithms. To tackle the problem, we introduce a new language representation model namely Word Graph Network (WGN). By introducing word graph, WGN integrates more syntactic structure information thus is qualified with stronger association and completion capability on detecting informal and incomplete violation comments in social networking scenarios. Our experimental results show that WGN outperforms than the existing state-of-the-art models and even performs best in simulation of real online environment.

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Titel: Word Graph Network: Understanding Obscure Sentences on Social Media for Violation Comment Detection
verfasst von: Dan Ma
Haidong Liu
Dawei Song
Verlag: Springer International Publishing
Buch: Natural Language Processing and Chinese Computing
Print ISBN: 978-3-030-60449-3

Electronic ISBN: 978-3-030-60450-9

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-60450-9_58

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