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Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data

Solymosi, R; Bowers, KJ; Fujiyama, T; (2018) Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data. British Journal Of Criminology , 58 (4) pp. 944-967. 10.1093/bjc/azx048. Green open access

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Abstract

New forms of data are now widely used in social sciences, and much debate surrounds their ideal application to the study of crime problems. Limitations associated with this data, including the subjective bias in reporting are often a point of this debate. In this article, we argue that by re-conceptualizing such data and focusing on their mode of production of crowdsourcing, this bias can be understood as a reflection of people’s subjective experiences with their environments. To illustrate, we apply the theoretical framework of signal crimes to empirical analysis of crowdsourced data from an online problem reporting website. We show how this approach facilitates new insight into people’s experiences and discuss implications for advancing research on perception of crime and place.

Type: Article
Title: Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bjc/azx048
Publisher version: https://doi.org/10.1093/bjc/azx048
Language: English
Additional information: Copyright © The Author 2017. Published by Oxford University Press on behalf of the Centre for Crime and Justice Studies (ISTD). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: crowdsourcing, disorder, new forms of data, perception of crime and place, signal crimes, signal disorder
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/1572528
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