Abstract
Hate speech may be the research focus of the interdisciplinary field of hate studies, but it is also a difficult phenomenon to define. Internationally, there are several detection studies on automatically detecting hate speech. They can be grouped according to two approaches: the first includes searching using only machine learning methods, while the second includes studies that combine automatic searching with human classification. The case study on anti-Gypsy hate in Italian on Twitter in the second half of 2020 falls into the second category, and its methods are outlined here. Based on the results (annotation as ‘hate’/‘non-hate’, identification of forms of rhetoric and anti-Gypsyism), the researchers propose classifying online content according to seven indicators called the ‘spectrum of online hate’.