Reducing and counter-acting hate speech on Social Media is a significant concern. Most of the proposed automatic methods are conducted exclusively on English and very few consistently labeled, non-English resources have been proposed. Learning to …
Language models have revolutionized the field of NLP. However, language models capture and proliferate hurtful stereotypes, especially in text generation. Our results show that **4.3% of the time, language models complete a sentence with a hurtful …
**Automatic Misogyny Identification (AMI)** is a **shared task** proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on **Italian tweets**, is organized into two subtasks: (1) Subtask A about misogyny and aggressiveness …
**Hate speech** may take different forms in online social environments. In this paper, we address the problem of automatic detection of misogynous language on **Italian tweets** by focusing both on raw text and stylometric profiles. The proposed …
During the last years, the phenomenon of **hate against women** increased exponentially especially in online environments such as microblogs. Although this alarming phenomenon has triggered many studies both from computational linguistic and machine …
The paper describes the organization of the SemEval 2019 Task 5 about the detection of **hate speech against immigrants and women** in **Spanish and English** messages extracted from Twitter. The task is organized in two related classification …