Inters8: A Corpus to Study Misogyny and Intersectionality on Twitter

Authors: Ivan Spada, Mirko Lai, Viviana Patti

Affiliation: Computer Science Department - University of Turin, Italy

Contacts: {ivan.spada, mirko.lai, viviana.patti}@unito.it

Conference: CLiC-it 2023, Venice, November 30 - December 2, 2023 (link)

Year: 2023

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WARNING: this repository contains examples of potentially offensive content.

Paper abstract

This paper presents our research conducted 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 schema designed to assess the presence of intersectional hatred.

Corpus

In order to comply with Twitter's terms and conditions, please contact the authors regarding information and uses of the Inters8 corpus.

References

If you use the resource, please cite:

@inproceedings{
  spada2023inters,
  title={Inters8: A Corpus to Study Misogyny and Intersectionality on Twitter},
  author={Ivan Spada and Mirko Lai and Viviana Patti},
  booktitle={Ninth Italian Conference on Computational Linguistics},
  year={2023},
  url={}
}

Repository

• annotation:
  • annotation_majority_vote.csv: annotation of a subset of 1500 tweets (majority vote)
  • annotation_schema.md: a novel annotation schema
  • annotators_table.md: annotators features
  • guidelines_ENG.md: annotation guidelines (English)
  • guidelines_ITA.md: annotation guidelines (Italian)
• targets:
  • targets-table.pdf: targets/dimensionalities table filled out during the analysis phase of the target subjects