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Simona Frenda is a Research Fellow at the University of Turin. She obtained the PhD in Computer Science in a cotutelle program between University of Turin (Italy) and Polytechnic University of Valencia (Spain). Her research interests involve sentiment analysis issues and, in particular, the impact of figurative language, such as irony, on automatic classification of texts online. Her PhD thesis focused on the implicitness and creativity in abusive contents from a multilingual and computational perspective. She is a member of the Associazione Italiana di Linguistica Computazionale (AILC) and, in the past, was a co-organizer of the HaSpeeDe share task about automatic identification of hate speech and stereotypes online and of the IronITA shared task about automatic detection of irony and sarcasm in hateful and political discussions online, respectively at EVALITA 2020 and 2018. In the last years, she is co-organizer of EMit shared task about emotion detection at EVALITA 2023. Moreover, she is working in the context of the STERHEOTYPES European project focused on the study of stereotypes in racial hoaxes from a linguistic, psychologist and computational perspective, and in the POPULUS project (Multilingual Perspective-aware NLU) in partnership with Amazon Alexa. She was co-organizer of the DeactivHate course for students of secondary school with the purpose to raise awareness on the spread of hate speech online and on how new AI technologies work; and currently, she is assistant in the course of "Elementi di basi di dati e Data Mining" with Professor Federica Cena. Moreover, she actively serves as Program Committee member and reviewer for various journals and conferences in the NLP field. Finally, as member of the Content-Centered Computing (CCC) group of the Computer Science Department at the University of Turin, she collaborated in the organization of meeting and seminars published in https://ccc.di.unito.it/.