Inters8: A Corpus to Study Misogyny and Intersectionality on Twitter

This paper presents our research on the detection of online misogyny on social media and its intersection with other hate categories. Focusing on the phenomenon of misogyny, we carried out a corpus-based data analysis around victims of online hate campaigns. Targets were selected to study how misogyny and sexism intersect with other categories of social hatred and discrimination such as xenophobia, racism, and Islamophobia. This study includes an event-driven analysis of hate on Twitter concerning specific targets, the process of developing the Inters8 corpus, and its manual annotation according to a novel multi-level scheme designed to assess the presence of intersectional hatred.