Title
Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter.
Abstract
Patriarchal behavior, such as other social habits, has been transferred online, appearing as misogynistic and sexist comments, posts or tweets. This online hate speech against women has serious consequences in real life, and recently, various legal cases have arisen against social platforms that scarcely block the spread of hate messages towards individuals. In this difficult context, this paper presents an approach that is able to detect the two sides of patriarchal behavior, misogyny and sexism, analyzing three collections of English tweets, and obtaining promising results.
Year
DOI
Venue
2019
10.3233/JIFS-179023
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Misogyny detection,sexism detection,linguistic analysis
Artificial intelligence,Mathematics education,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
36
SP5
1064-1246
Citations 
PageRank 
References 
2
0.41
0
Authors
4
Name
Order
Citations
PageRank
Simona Frenda120.74
Bilal Ghanem2128.07
Manuel Montes-Y-Gómez363883.97
paolo rosso41831188.74