Auditing the representation of migrants in image web search results
Abstract: Search engines serve as information gatekeepers on a multitude of topics that are prone to gender, ethnicity, and race misrepresentations. In this paper, we specifically look at the image search representation of migrant population groups that are often subjected to discrimination and biased representation in mainstream media, increasingly so with the rise of right-wing populist actors in the Western countries. Using multiple (n = 200) virtual agents to simulate human browsing behavior in a controlled environment, we collect image search results related to various terms referring to migrants (e.g., expats, immigrants, and refugees, seven queries in English and German used in total) from the six most popular search engines. Then, with the aid of manual coding, we investigate which features are used to represent these groups and whether the representations are subjected to bias. Our findings indicate that search engines reproduce ethnic and gender biases common for mainstream media r
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
Veröffentlichungsversion
begutachtet (peer reviewed)
In: Humanities and Social Sciences Communications ; 9 (2022) ; 1-16
- Klassifikation
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Sozialwissenschaften, Soziologie, Anthropologie
- Ereignis
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Veröffentlichung
- (wo)
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Mannheim
- (wer)
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SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
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2022
- Urheber
- DOI
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10.1057/s41599-022-01144-1
- URN
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urn:nbn:de:0168-ssoar-81396-5
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:53 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Urman, Aleksandra
- Makhortykh, Mykola
- Ulloa, Roberto
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
Entstanden
- 2022
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