Gender bias is more exaggerated in online images than in text

Bas Hofstra () and Anne Maaike Mulders ()

Nature, 2024, vol. 626, issue 8001, 960-961

Abstract: A big-data analysis shows that men are starkly over-represented in online images, and that gender bias is stronger in images compared with text. Such images could influence enduring gender biases in our offline lives.

Keywords: Sociology; Information technology (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/d41586-024-00291-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:nat:nature:v:626:y:2024:i:8001:d:10.1038_d41586-024-00291-6

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

DOI: 10.1038/d41586-024-00291-6

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

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