Confronting bias in the online representation of pregnancy

Loes Bogers, Sabine Niederer, Federica Bardelli, Carlo De Gaetano

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
1 Downloads (Pure)


This article interrogates platform-specific bias in the contemporary algorithmic media landscape through a comparative study of the representation of pregnancy on the Web and social media. Online visual materials such as social media content related to pregnancy are not void of bias, nor are they very diverse. The case study is a cross-platform analysis of social media imagery for the topic of pregnancy, through which distinct visual platform vernaculars emerge. The authors describe two visualization methods that can support comparative analysis of such visual vernaculars: the image grid and the composite image. While platform-specific perspectives range from lists of pregnancy tips on Pinterest to pregnancy information and social support systems on Twitter, and pregnancy humour on Reddit, each of the platforms presents a predominantly White, able-bodied and heteronormative perspective on pregnancy.
Original languageEnglish
Pages (from-to)1037-1059
JournalConvergence: The International Journal of Research into New Media Technologies
Issue number5-6
Publication statusPublished - Dec 2020


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