Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP

Cristina Bosco*, Viviana Patti, Simona Frenda, Alessandra Teresa Cignarella, Marinella Paciello, Francesca D'Errico

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

The generation of stereotypes allows us to simplify the cognitive complexity we have to deal with in everyday life. Stereotypes are extensively used to describe people who belong to a different ethnic group, particularly in racial hoaxes and hateful content against immigrants. This paper addresses the study of stereotypes from a novel perspective that involves psychology and computational linguistics both. On the one hand, it describes an Italian social media corpus built within a social psychology study, where stereotypes and related forms of discredit were made explicit through annotation. On the other hand, it provides some lexical analysis, to bring out the linguistic features of the messages collected in the corpus, and experiments for validating this annotation scheme and its automatic application to other corpora in the future. The main expected outcome is to shed some light on the usefulness of this scheme for training tools that automatically detect and label stereotypes in Italian.
Original languageEnglish
Article number103118
JournalInformation Processing & Management
Volume60
Issue number1
Early online date1 Nov 2022
DOIs
Publication statusPublished - Jan 2023

Keywords

  • Stereotypes
  • Social psychology
  • Natural language processing
  • Social media
  • Lexical analysis
  • Corpus
  • Linguistic annotation
  • Machine learning
  • BERT

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