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’.
Pasta, S., Hate Speech Research: Algorithmic and Qualitative Evaluations. A Case Study of Anti-Gypsy Hate on Twitter, <<REM>>, 2023; 15 (1): 130-139. [doi:10.2478/rem-2023-0017] [https://hdl.handle.net/10807/224367]
Hate Speech Research: Algorithmic and Qualitative Evaluations. A Case Study of Anti-Gypsy Hate on Twitter
Pasta, Stefano
2023
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’.File | Dimensione | Formato | |
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