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Article
Detecting Misogynous Tweets
School of Engineering and Technology Publications
  • R. Ahluwalia
  • E. Shcherbinina
  • E. Callow
  • Anderson Nascimento, University of Washington Tacoma
  • Martine De Cock
Publication Date
1-1-2018
Document Type
Conference Proceeding
Abstract

Social media companies struggle to control the quality of the content on their platforms. The sheer amount of user-generated content uploaded on a daily basis far exceeds what can be screened by human curators, fuelling the need for intelligent detection algorithms that can automatically flag inappropriate content. In this paper, we present machine learning models that can identify instances of aggression and hate speech towards women in tweets. In particular, we present the system that we submitted for the shared task on automatic misogyny identification at IberEval 2018. © 2018 CEUR-WS. All Rights Reserved.

Citation Information
R. Ahluwalia, E. Shcherbinina, E. Callow, Anderson Nascimento, et al.. "Detecting Misogynous Tweets" Vol. 2150 (2018) p. 242 - 248
Available at: http://works.bepress.com/anderson-nascimento/24/