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Mass participation during emergency response: event-centric crowd-sourcing in humanitarian mapping

Dittus, M; Quattrone, G; Capra, L; (2017) Mass participation during emergency response: event-centric crowd-sourcing in humanitarian mapping. In: Lee, CP and Poltrock, S and Barkhuus, L and Borges, M and Kellogg, W, (eds.) CSCW '17: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. (pp. pp. 1290-1303). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

Crowdsourcing platforms have become important information providers after disaster events. While they can build on some prior experiences, it is not yet well understood how contributor capacity for such activities is constituted. To what extent are initiatives building a dormant task force that springs to action when it is needed? Alternatively, do they mainly rely on the recruitment of new contributors during disaster events, possibly at the expense of contribution quality? We seek to develop a better understanding of these relationships, using the example of the Humanitarian OpenStreetMap Team. In a large-scale quantitative study, we assess the outcomes of 26 campaigns with almost 20,000 participants. We find that event-centric campaigns can be significant recruiting and reactivation events, however that this is not guaranteed. Our analytical methods provide a means of interpreting key differences in outcomes. We close with recommendations relating to the promotion and coordination of event-centric campaigns in HOT and related platforms.

Type: Proceedings paper
Title: Mass participation during emergency response: event-centric crowd-sourcing in humanitarian mapping
Event: 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17)
Location: Portland, United States
Dates: 25 February – 1 March 2017
ISBN-13: 9781450343350
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2998181.2998216
Publisher version: https://doi.org/10.1145/2998181.2998216
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL > Provost and Vice Provost Offices
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 Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1515026
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