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Collabmap: crowdsourcing maps for emergency planning

Record type: Conference or Workshop Item (Paper)

In this paper, we present a software tool to help emergency planners at Hampshire County Council in the UK to create maps for high-fidelity crowd simulations that require evacuation routes from buildings to roads. The main feature of the system is a crowdsourcing mechanism that breaks down the problem of creating evacuation routes into microtasks that a contributor to the platform can execute in less than a minute. As part of the mechanism we developed a concensus-based trust mechanism that filters out incorrect contributions and ensures that the individual tasks are complete and correct. To drive people to contribute to the platform, we experimented with different incentive mechanisms and applied these over different time scales, the aim being to evaluate what incentives work with different types of crowds, including anonymous contributors from Amazon Mechanical Turk. The results of the 'in the wild' deployment of the system show that the system is effective at engaging contributors to perform tasks correctly and that users respond to incentives in different ways. More specifically, we show that purely social motives are not good enough to attract a large number of contributors and that contributors are averse to the uncertainty in winning rewards. When taken altogether, our results suggest that a combination of incentives may be the best approach to harnessing the maximum number of resources to get socially valuable tasks (such for planning applications) performed on a large scale.

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Ramchurn, Sarvapali D., Huynh, Trung Dong, Venanzi, Matteo and Shi, Bing (2013) Collabmap: crowdsourcing maps for emergency planning At The 5th Annual ACM Web Science Conference, France. 02 - 04 May 2013. 10 pp, pp. 326-335. (doi:10.1145/2464464.2464508).

More information

Published date: 3 May 2013
Venue - Dates: The 5th Annual ACM Web Science Conference, France, 2013-05-02 - 2013-05-04
Organisations: Web & Internet Science, Agents, Interactions & Complexity


Local EPrints ID: 350677
ISBN: 978-1-4503-1889-1
PURE UUID: 04ac9e69-c179-41c6-ab6b-d598e0b968bb
ORCID for Sarvapali D. Ramchurn: ORCID iD
ORCID for Trung Dong Huynh: ORCID iD

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Date deposited: 08 Apr 2013 13:24
Last modified: 18 Jul 2017 04:32

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Author: Sarvapali D. Ramchurn ORCID iD
Author: Trung Dong Huynh ORCID iD
Author: Matteo Venanzi
Author: Bing Shi

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