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Using Crowdsourced Data to Study Crime and Place

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  • Buil-Gil, David

    (University of Manchester)

  • Solymosi, Reka

Abstract

Crowdsourcing refers to the practise of enlisting the knowledge, experience or skills of a large number of people (the crowd) through some digital platform to collect data towards a collaborative project. Crowdsourcing can generate large volumes of data in relatively little time at a very small cost, and can be useful for research, strategic police management and many other purposes. To make effective use of crowdsourced data, it is important to understand its key strengths to emphasize, and limitations to mitigate. In this chapter we highlight the main strengths and weaknesses of crowdsourcing, and illustrate how to acquire, make sense of, and critically evaluate crowdsourced data to study crime and place. We present a step-by-step exemplar study using crowdsourced data from a platform called Place Pulse, where people rate their feelings of safety between different areas. Taking the case study of Atlanta, Georgia, we work through analyzing and interpreting these data while highlighting how to emphasize and evaluate the strengths and limitations of crowdsourcing. Exercises are presented using R software.

Suggested Citation

  • Buil-Gil, David & Solymosi, Reka, 2020. "Using Crowdsourced Data to Study Crime and Place," SocArXiv 9ntk6, Center for Open Science.
    • Handle: RePEc:osf:socarx:9ntk6
    DOI: 10.31219/osf.io/9ntk6
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    References listed on IDEAS

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    2. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
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