“An image hurts more than 1000 words?”

Author:

Oehmer-Pedrazzi Franziska1,Pedrazzi Stefano2

Affiliation:

1. University of Applied Sciences of the Grisons Bern Switzerland

2. University of Fribourg Fribourg Switzerland

Abstract

Abstract Visual content captures attention, is easy to understand, and is more likely to be remembered. However, it is not limited to conveying informative content; it can also be used to propagate hate. While existing research has predominantly focused on textual hate speech, this study aims to address a research gap by analyzing the characteristics of visual hate, including its channels, intensity, sources, and targets, through a standardized manual content analysis. The hate images were collected through the citizen science approach of data donation. Findings highlight that transgender individuals and migrants are the primary targets of visual hate. It reveals a presence of hate images not only on communication platforms but also in various intermediaries and journalistic media. Half of these images use factual or humorous methods to discriminate against individuals or groups, while an equal number adopt a highly aggressive tone. The study suggests governance measures to combat this issue effectively.

Publisher

Walter de Gruyter GmbH

Reference55 articles.

1. Article 19. (2015). ‘Hate Speech’ explained. A toolkit. https://www.article19.org/data/files/medialibrary/38231/’Hate-Speech’-Explained---A-Toolkit-%282015-Edition%29.pdf

2. Askanius, T. (2021). On frogs, monkeys, and execution memes: Exploring the humor-hate nexus at the intersection of Neo-Nazi and Alt-Right movements in Sweden. Television & New Media, 22(2), 147–165. https://doi.org/10.1177/1527476420982234

3. Baider, F. H. (2020). Pragmatics lost? Overview, synthesis and proposition in defining online hate speech. Pragmatics and Society, 11(2), 196–218. https://doi.org/10.1075/ps.20004.bai

4. Ben-David, A., & Matamoros-Fernández, A. (2016). Hate speech and covert discrimination on social media: Monitoring the Facebook pages of extreme-right political parties in Spain. International Journal of Communication, 10, 1167–1193 https://ijoc.org/index.php/ijoc/article/view/3697

5. Bilewicz, M., & Soral, W. (2020). Hate speech epidemic: The dynamic effects of derogatory language on intergroup relations and political radicalization. Political Psychology, 41(1), 3–33. https://doi.org/10.1111/pops.12670

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