Abusive Language Detection and Characterization of Twitter Behavior

Autor:	Davis, Dincy, Murali, Reena, Babu, Remesh
Rok vydání:	2020
Předmět:	Computer Science - Computation and Language Computer Science - Information Retrieval
Zdroj:	International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, July 2020
Druh dokumentu:	Working Paper
Popis:	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. Comment: 7 pages, 7 figures and 8 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2009.14261 Zobrazit plný text záznamu View this record from Arxiv