Work

Detecting Hate Speech Against Women in English Tweets

Year: 2018

Type: book-chapter

Abstract: Hate speech is prevalent in social media platforms. Systems that can automatically detect offensive content are of great value to assist human curators with removal of hateful language. In this paper, we present machine learning models developed at UW Tacoma for detection of misogyny, i.e. hate speech against women, in English tweets, and the results obtained with these models in the shared task for Automatic Misogyny Identification (AMI) at EVALITA2018.

Source: Accademia University Press eBooks

DOI: 10.4000/books.aaccademia.4698

Authors: Resham Ahluwalia, Himani Soni, Edward Callow, Anderson Nascimento, Martine De Cock

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Gender equality, Reduced inequalities

Open Access status: hybrid

Funders: Università degli Studi di Napoli Federico II, National Research Council Canada

OpenAlex ID: W2907894232

FWCI: 6.166

Cites: 11

Cited by: 39

Related to: 10