@inproceedings{damo-etal-2025-hodiat,
title = "{HODIAT}: A Dataset for Detecting Homotransphobic Hate Speech in {I}talian with Aggressiveness and Target Annotation",
author = "Damo, Greta and
Cignarella, Alessandra Teresa and
Caselli, Tommaso and
Patti, Viviana and
Nozza, Debora",
editor = "Calabrese, Agostina and
de Kock, Christine and
Nozza, Debora and
Plaza-del-Arco, Flor Miriam and
Talat, Zeerak and
Vargas, Francielle",
booktitle = "Proceedings of the The 9th Workshop on Online Abuse and Harms (WOAH)",
month = aug,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.woah-1.11/",
pages = "124--135",
ISBN = "979-8-89176-105-6",
abstract = "The escalating spread of homophobic and transphobic rhetoric in both online and offline spaces has become a growing global concern, with Italy standing out as one of the countries where acts of violence against LGBTQIA+ individuals persist and increase year after year. This short paper study analyzes hateful language against LGBTQIA+ individuals in Italian using novel annotation labels for aggressiveness and target. We assess a range of multilingual and Italian language models on this newannotation layers across zero-shot, few-shot, and fine-tuning settings. The results reveal significant performance gaps across models and settings, highlighting the limitations of zero- and few-shot approaches and the importance of fine-tuning on labelled data, when available, to achieve high prediction performance."
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%0 Conference Proceedings
%T HODIAT: A Dataset for Detecting Homotransphobic Hate Speech in Italian with Aggressiveness and Target Annotation
%A Damo, Greta
%A Cignarella, Alessandra Teresa
%A Caselli, Tommaso
%A Patti, Viviana
%A Nozza, Debora
%Y Calabrese, Agostina
%Y de Kock, Christine
%Y Nozza, Debora
%Y Plaza-del-Arco, Flor Miriam
%Y Talat, Zeerak
%Y Vargas, Francielle
%S Proceedings of the The 9th Workshop on Online Abuse and Harms (WOAH)
%D 2025
%8 August
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-105-6
%F damo-etal-2025-hodiat
%X The escalating spread of homophobic and transphobic rhetoric in both online and offline spaces has become a growing global concern, with Italy standing out as one of the countries where acts of violence against LGBTQIA+ individuals persist and increase year after year. This short paper study analyzes hateful language against LGBTQIA+ individuals in Italian using novel annotation labels for aggressiveness and target. We assess a range of multilingual and Italian language models on this newannotation layers across zero-shot, few-shot, and fine-tuning settings. The results reveal significant performance gaps across models and settings, highlighting the limitations of zero- and few-shot approaches and the importance of fine-tuning on labelled data, when available, to achieve high prediction performance.
%U https://aclanthology.org/2025.woah-1.11/
%P 124-135
Markdown (Informal)
[HODIAT: A Dataset for Detecting Homotransphobic Hate Speech in Italian with Aggressiveness and Target Annotation](https://aclanthology.org/2025.woah-1.11/) (Damo et al., WOAH 2025)
ACL