Hill, R.L., Kennedy, H. and Gerrard, Y. (2016) Visualizing Junk: Big Data Visualizations and the need for Feminist Data Studies. Journal of Communication Inquiry, 40 (4). pp. 331-350. ISSN 0196-8599
Abstract
The datafication of culture has led to an increase in the circulation of data visualizations. In their production, visualizers draw on historical antecedents which define what constitutes a good visualization. In their reception, audiences similarly draw on experiences with visualizations and other visual forms to categorize them as good or bad. Whilst there are often sound reasons for such assessments, the gendered dimensions of judgements of cultural artefacts like data visualizations cannot be ignored. In this paper, we highlight how definitions of visualizations as bad are sometimes gendered. In turn, this gendered derision is often entangled with legitimate criticisms of poor visualization execution, making it hard to see and so normalised. This, we argue, is a form of what Gill (2011) calls flexible sexism, and it is why there is a need not just for feminist critiques of big data, but for feminist data studies – that is, feminists doing big data and data visualization.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2016. This is an author produced version of a paper subsequently published in Journal of Communication Enquiry. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | big data; data visualization; feminist data studies; gender; flexible sexism |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Sociological Studies (Sheffield) |
Funding Information: | Funder Grant number ARTS AND HUMANITIES RESEARCH COUNCIL (AHRC) AH/L009986/2 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Aug 2016 14:17 |
Last Modified: | 30 Nov 2016 18:43 |
Published Version: | http://dx.doi.org/10.1177/0196859916666041 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/0196859916666041 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103393 |