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

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Application and Analysis of a Multi-layered Scheme for Irony on the Italian Twitter Corpus TWITTIRÒ., , , and . LREC, European Language Resources Association (ELRA), (2018)Recognizing Hate with NLP: The Teaching Experience of the #DeactivHate Lab in Italian High Schools., , , , , and . CLiC-it, volume 3033 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations., , , , , , , , , and . CoRR, (2020)Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP., , , , , and . Inf. Process. Manag., 60 (1): 103118 (2023)Treebanking user-generated content: a UD based overview of guidelines, corpora and unified recommendations., , , , , , , , , and . Lang. Resour. Evaluation, 57 (2): 493-544 (2023)Do Dependency Relations Help in the Task of Stance Detection?, , and . Insights@ACL, page 10-17. Association for Computational Linguistics, (2022)Multilingual stance detection in social media political debates., , , , , and . Comput. Speech Lang., (2020)Dependency Syntax in the Automatic Detection of Irony and Stance.. Proces. del Leng. Natural, (2022)The unbearable hurtfulness of sarcasm., , , , , and . Expert Syst. Appl., (2022)O-Dang! The Ontology of Dangerous Speech Messages., , , , , , , and . CoRR, (2022)