misogyny detection

AMI @ EVALITA2020: Automatic Misogyny Identification

**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 …

Profiling Italian Misogynist: An Empirical Study

**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 …

Hate Speech and Misogyny Detection

How fair Machine Learning models could solve Hate Speech and Misogyny Detection?

Unintended Bias in Misogyny Detection

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 …

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

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 …

Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI)

**Automatic Misogyny Identification** (AMI) is a new **shared task** proposed for the first time at the Evalita 2018 evaluation campaign. The AMI challenge, based on both **Italian and English** tweets, is distinguished into two subtasks, i.e. …