Back
rohrbachetal_2026_vpnauditofalgorithmicunderrepresentation
Journal article

+ 1 other files

The Prevalence and Consequences of Women’s Algorithmic Underrepresentation in Cross-National Political Google Searches

BP2-STS

  • 2026
Published in:
  • Political Communication. - 2026, p. 1-23
Algorithms
Gender bias
Representation
Search engines
Artificial intelligence
English Search engines like Google have become major information gatekeepers that use artificial intelligence (AI) to determine who and what voters find when searching for political information. Yet there is concern that biases in algorithmically curated representation of women politicians in online search results mirror and amplify structural inequalities and therefore further reduce women’s electoral chances. We empirically assess the prevalence and consequences of algorithmic gender bias in political Google searches in a series of four studies. First, we conduct two multinational algorithm audits of political image searches (study 1: 56 countries and 6,363 images; study 2: 11 countries and 152,098 images) to assess women’s quantitative representation in search results. We find that women politicians’ algorithmic representation on average accurately mirrors the actual gender composition of legislative bodies while consistently remaining below absolute gender parity. Second, we show in two online experiments from three different samples (1,388 respondents in total) how more extreme cases of algorithmic underrepresentation can influence human perceptions of the political reality and actively reinforce a white and masculinized view of politics. These misperceptions act as a casual conduit through which algorithmic biases can not only diminish the perceived chances of winning an election for minoritized candidates but also result in voters feeling that their voices matter less. Together, the results highlight the risk that, under certain conditions, algorithmic systems like search engines can negatively impact electoral processes.
Faculty
Faculté des sciences économiques et sociales et du management
Department
Département des sciences de la communication et des médias
Language
  • English
Classification
Information, communication and media sciences
License
CC BY
Open access status
green
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/335584
Other files
postdatareview_vpn_mascpolitics_supportingmaterials_blinded
postdatareview_vpn_mascpolitics_supportingmaterials_blinded
Statistics
Document views: 55 File downloads:
  • rohrbachetal_2026_vpnauditofalgorithmicunderrepresentation: 2
  • postdatareview_vpn_mascpolitics_supportingmaterials_blinded: 3