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Publication Detail
Mapping community engagement with urban crowd-sourcing
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Conference Proceeding
  • Authors:
    Hristova D, Mashhadi A, Quattrone G, Capra L
  • Publication date:
  • Pagination:
    14, 19
  • Journal:
    AAAI Workshop - Technical Report
  • Volume:
  • Status:
Cities are highly dynamic entities, with urban elements such as businesses, cultural and social Points-of-Interests (POIs), housing, transportation and the like, continuously changing. In order to maintain accurate spatial information in these settings, crowd-sourcing models of data collection, such as in OpenStreetMap (OSM), have come under investigation. Like many crowd-sourcing platforms (e.g., Wikipedia), these geowikis exhibit tailing-off activity, bringing into question their long-term viability. In this paper, we begin an investigation into the sustainability of urban crowd-sourcing, by studying the network structure and geographical mapping of implicit communities of contributors in OSM. We observe that spatially clustered crowd-sourcing communities produce higher coverage than those with looser geographic affinity. We discuss the positive implications that this has on the future of urban crowd-sourcing. Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
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