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Crime applications and social machines: crowdsourcing sensitive data

Byrne Evans, Maire, O'Hara, Kieron, Tiropanis, Thanassis and Webber, Craig (2013) Crime applications and social machines: crowdsourcing sensitive data At SOCIAM: The Theory and Practice of Social Machines, Brazil.

Record type: Conference or Workshop Item (Other)


The authors explore some issues with the United Kingdom (U.K.) crime reporting and recording systems which currently produce Open Crime Data. The availability of Open Crime Data seems to create a potential data ecosystem which would encourage crowdsourcing, or the creation of social machines, in order to counter some of these issues. While such solutions are enticing, we suggest that in fact the theoretical solution brings to light fairly compelling problems, which highlight some limitations of crowdsourcing as a means of addressing Berners-Lee’s “social constraint.” The authors present a thought experiment – a Gendankenexperiment - in order to explore the implications, both good and bad, of a social machine in such a sensitive space and suggest a Web Science perspective to pick apart the ramifications of this thought experiment as a theoretical approach to the characterisation of social machines

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Submitted date: April 2013
Published date: 13 May 2013
Venue - Dates: SOCIAM: The Theory and Practice of Social Machines, Brazil, 2013-05-13
Organisations: Electronics & Computer Science, Social Sciences


Local EPrints ID: 351275
PURE UUID: bff852f0-1b2b-4b7f-8d7b-a0eaf50a678d
ORCID for Thanassis Tiropanis: ORCID iD

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Date deposited: 22 Apr 2013 09:19
Last modified: 18 Jul 2017 04:27

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Author: Maire Byrne Evans
Author: Kieron O'Hara
Author: Craig Webber

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