Auditing the representation of migrants in image web search results

Aleksandra Urman (), Mykola Makhortykh and Roberto Ulloa
Additional contact information
Aleksandra Urman: University of Zurich
Mykola Makhortykh: University of Bern
Roberto Ulloa: GESIS - Leibniz Institute for the Social Sciences

Palgrave Communications, 2022, vol. 9, issue 1, 1-16

Abstract: 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 representations of different subgroups of migrant population. For instance, migrant representations tend to be highly racialized, and female migrants as well as migrants at work tend to be underrepresented in the results. Our findings highlight the need for further algorithmic impact auditing studies in the context of representation of potentially vulnerable groups in web search results.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41599-022-01144-1 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01144-1

Ordering information: This journal article can be ordered from
https://www.nature.com/palcomms/about

DOI: 10.1057/s41599-022-01144-1

Access Statistics for this article

More articles in Palgrave Communications from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().