PoliTeam @ AMI: Improving Sentence Embedding Similaritywith Misogyny Lexicons for Automatic Misogyny Identificationin Italian Tweets

Abstract

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it).This volume includes the reports of both task organisers and participants to all of the EVALITA 2020 challenges. In the 2020 edition, we coordinated the organization of 14 different tasks belonging to five research areas, being: (i) Affect, Hate, and Stance, (ii) Creativity and Style, (iii) New Challenges in Long-standing Tasks, (iv) Semantics and Multimodality, Time and Diachrony.The volume is opened by an overview to the EVALITA 2020 campaign, in which we describe the tasks, provide statistics on the participants and task organizers as well as our supporting sponsors. The abstract of the keynote speech made by Preslav Nakov titled "Flattening the Curve of the COVID-19 Infodemic: These Evaluation Campaigns Can Help!" is also included in this collection.Due to the 2020 COVID-19 pandemic, the traditional workshop was held online, where several members of the Italian NLP Community presented the results of their research. Despite the circumstances, the workshop represented an occasion for all participants from both academic institutions and private companies to disseminate their work and results and to share ideas through online sessions dedicated to each task and a general discussion during the plenary event.We carried on with the tradition of the "Best system across tasks" award. As in 2018, it represented an incentive for students, IT developers and researchers to push the boundaries of the state of the art by facing tasks in new ways, even if not winning.

Measuring Harmful Sentence Completion in Language Models for LGBTQIA+ Individuals

“…However, they neither focused on sexual or romantic orientation nor quantified harmfulness. Research in hate speech detection considering gender and sexuality have mostly focus on sexism (Fersini et al, 2018;Basile et al, 2019;Chiril et al, 2020;Fersini et al, 2020a,b;Attanasio and Pastor, 2020;Zein-ert et al, 2021;Mulki and Ghanem, 2021;Nozza, 2021;Attanasio et al, 2022a,b). Few recent works covered hate speech on the basis of sexual orientation (Ousidhoum et al, 2019;Mollas et al, 2022;Kennedy et al, 2022;Chakravarthi et al, 2022;…”

Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection

“…Several NLP approaches have been proposed for the task of hate speech detection (Qian et al, 2018;Indurthi et al, 2019;Vidgen et al, 2021;Fersini et al, 2020a;Attanasio and Pastor, 2020;Kennedy et al, 2020;Attanasio et al, 2022b, inter alia). While ensemble modeling has been proven to be effective for several tasks in NLP (Garmash and Monz, 2016;Nozza et al, 2016;Fadel et al, 2019;Bashmal and AlZeer, 2021), a limited number of research work have investigated its potentiality for hate speech detection (Plaza-del Arco et al, 2019;Ramakrishnan et al, 2019;Zimmer-man et al, 2018).…”

HATE-ITA: Hate Speech Detection in Italian Social Media Text

“…National evaluation campaigns and shared tasks played a significant role in releasing non-English corpora for hate speech detection (Wiegand et al, 2018;Mulki and Ghanem, 2021;Basile et al, 2019;Ptaszynski et al, 2019). Indeed, the research of hate speech detection in Italian in mono-lingual settings mainly revolves around the datasets (Fersini et al, 2018;Sanguinetti et al, 2020;Fersini et al, 2020b) released for shared tasks (Bakarov, 2018;Cimino et al, 2018;Attanasio and Pastor, 2020;Lees et al, 2020;Lavergne et al, 2020;Fersini et al, 2020a;Attanasio et al, 2022a, inter alia).…”