There’s no such thing as the perfect map: quantifying bias in spatial crowd-sourcing datasets

Quattrone, Giovanni ORCID: https://orcid.org/0000-0001-9219-8437, Capra, Licia and De Meo, Pasquale (2015) There’s no such thing as the perfect map: quantifying bias in spatial crowd-sourcing datasets. Cosley, Dan, Forte, Andrea, Ciolfi, Luigina and McDonalld, David, eds. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. In: CSCW 2015, 14-18 May 2015, Vancouver, Canada. ISBN 9781450329224. [Conference or Workshop Item] (doi:10.1145/2675133.2675235)

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Abstract

Crowd-sourcing has become a popular form of computer mediated collaborative work and OpenStreetMap represents one of the most successful crowd-sourcing systems, where the goal of building and maintaining an accurate global map of the world is being accomplished by means of contributions made by over 1.2M citizens. However, within this apparently large crowd, a tiny group of highly active users is responsible for the mapping of almost all the content. One may thus wonder to what extent the information being mapped is biased towards the interests and agenda of this group of users. In this paper, we present a method to quantitatively measure content bias in crowd-sourced geographic information. We then apply the method to quantify content bias across a three-year period of OpenStreetMap mapping in 40 countries. We find almost no content bias in terms of what is being mapped, but significant geographic bias; furthermore, we find that bias in terms of meticulousness varies with culture.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 29155
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Depositing User: Giovanni Quattrone
Date Deposited: 12 Jan 2021 09:43
Last Modified: 12 Jan 2021 09:43
URI: https://eprints.mdx.ac.uk/id/eprint/29155

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