Hate Speech Research: Algorithmic and Qualitative Evaluations. A Case Study of Anti-Gypsy Hate on Twitter
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| Title: | Hate Speech Research: Algorithmic and Qualitative Evaluations. A Case Study of Anti-Gypsy Hate on Twitter |
|---|---|
| Language: | English |
| Authors: | Pasta, Stefano (ORCID |
| Source: | Research on Education and Media. Jun 2023 15(1):130-139. |
| Availability: | Sciendo, a company of De Gruyter Poland. 32 Zuga Street, 01-811 Warsaw, Poland. Tel: +48-22-701-5015; e-mail: info@sciendo.com; Web site: https://www.sciendo.com |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Social Bias, Antisocial Behavior, Social Media, Migrants, Minority Groups, Artificial Intelligence, Automation, Foreign Countries, Research Methodology, Racism |
| Geographic Terms: | Italy |
| DOI: | 10.2478/rem-2023-0017 |
| ISSN: | 2037-0830 2037-0849 |
| 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'. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Accession Number: | EJ1364776 |
| Database: | ERIC |
| 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'. |
|---|---|
| ISSN: | 2037-0830 2037-0849 |
| DOI: | 10.2478/rem-2023-0017 |
