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Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP
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.
Keywords:Stereotypes  Social psychology  Natural language processing  Social media  Lexical analysis  Corpus  Linguistic annotation  Machine learning  BERT
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