paper-with-me

Papers

Abusive Language Detection and Characterization of Twitter Behavior

2020-09-26 · Davis Dincy, Murali Reena, Babu Remesh

In this work, abusive language detection in online content is performed using Bidirectional Recurrent Neural Network (BiRNN) method. Here the main objective is to focus on various forms of abusive behaviors on Twitter and to detect whether a speech is abusive or not. The results are compared for various abusive behaviors in social media, with Convolutional Neural Netwrok (CNN) and Recurrent Neural Network (RNN) methods and proved that the proposed BiRNN is a better deep learning model for automatic abusive speech detection.

📄 PDF Abstract BibTeX arXiv:2009.14261

Code (0)

등록된 구현이 없습니다.

Tasks

Abusive Language

Similar Papers 제목 키워드 기반

A Unified Deep Learning Architecture for Abuse Detection

2018-02-01 · Antigoni-Maria Founta, Despoina Chatzakou, Nicolas Kourtellis, Jeremy Blackburn 외

Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms. In recent years, such diverse abusive behaviors have been manifes…

Abuse DetectionBlockingDeep Learning

Abusive Language Detection with Graph Convolutional Networks

2019-04-05 · NAACL 2019 6 · Pushkar Mishra, Marco del Tredici, Helen Yannakoudakis, Ekaterina Shutova

Abuse on the Internet represents a significant societal problem of our time. Previous research on automated abusive language detection in Twitter has shown that community-based profiling of users is a promising technique…

Abuse Detection

One-step and Two-step Classification for Abusive Language Detection on Twitter

2017-06-05 · WS 2017 8 · Ji Ho Park, Pascale Fung

Automatic abusive language detection is a difficult but important task for online social media. Our research explores a two-step approach of performing classification on abusive language and then classifying into specifi…

Abuse DetectionAbusive LanguageClassificationGeneral Classification+2

Comparative Studies of Detecting Abusive Language on Twitter

2018-08-30 · WS 2018 10 · Younghun Lee, Seunghyun Yoon, Kyomin Jung

The context-dependent nature of online aggression makes annotating large collections of data extremely difficult. Previously studied datasets in abusive language detection have been insufficient in size to efficiently tr…

Abuse DetectionAbusive LanguageClusteringHate Speech Detection+2

L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language

2019-08-01 · WS 2019 8 · Hala Mulki, Hatem Haddad, Chedi Bechikh Ali, Halima Alshabani

Hate speech and abusive language have become a common phenomenon on Arabic social media. Automatic hate speech and abusive detection systems can facilitate the prohibition of toxic textual contents. The complexity, infor…

Abusive LanguageHate Speech Detection