The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
How a personalized geowiki can help bicyclists share information more effectively
Proceedings of the 2007 international symposium on Wikis
The convergence of social and technological networks
Communications of the ACM - Remembering Jim Gray
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Eliciting and focusing geographic volunteer work
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Lurking? cyclopaths?: a quantitative lifecycle analysis of user behavior in a geowiki
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 20th international conference on World wide web
Proceedings of the 7th International Symposium on Wikis and Open Collaboration
Proceedings of the fifth ACM international conference on Web search and data mining
YouTube around the world: geographic popularity of videos
Proceedings of the 21st international conference on World Wide Web
Information diffusion and external influence in networks
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
The hidden image of the city: sensing community well-being from urban mobility
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Putting ubiquitous crowd-sourcing into context
Proceedings of the 2013 conference on Computer supported cooperative work
On the accuracy of urban crowd-sourcing for maintaining large-scale geospatial databases
Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration
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Urban crowd-sourcing has become a popular paradigm to harvest spatial information about our evolving cities directly from citizens. OpenStreetMap is a successful example of such paradigm, with an accuracy of its user-generated content comparable to that of curated databases (e.g., Ordnance Survey). Coverage is however low and most importantly non-uniformly distributed across the city. Being able to model the spontaneous growth of digital information in these domains is required, so to be able to plan interventions aimed at gathering content about areas that would otherwise be neglected. Inspired by models of physical urban growth developed by urban planners, we build a model of digital growth of crowd-sourced spatial information that is both easy to interpret and dynamic, so to be able to determine what factors impact growth and how these change over time. We build and test the model against five years of OpenStreetMap data for the city of London, UK. We then run the model against two other cities, chosen for their different physical and digital growth's characteristics, so to stress-test the model. We conclude with a discussion of the implications of this work on both developers and users of urban crowd-sourcing applications.