Title
Detecting Hate Speech Against Women in English Tweets
Publication Date
2018
Document Type
Conference Proceeding
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. © 2018 CEUR-WS. All Rights Reserved.
Volume
2263
Recommended Citation
Ahluwalia, R.; Soni, H.; Callow, E.; Nascimento, A.; and De Cock, M., "Detecting Hate Speech Against Women in English Tweets" (2018). School of Engineering and Technology Publications. 330.
https://digitalcommons.tacoma.uw.edu/tech_pub/330