Crooks, A. T., Hudson-Smith, A., M., Milton, R., and Batty, M. (2009), Crowdsourcing Spatial Surveys and Mapping, in Fairbairn, D. (ed.), Proceedings of the 17th Geographical Information Systems Research UK Conference, Durham University, England, pp 263-269. (pdf)
We thought we would put it on-line, to gauge peoples thoughts about it as it is the product of the crowd. Any comments and suggestions are most welcome.
Why blog about this work? It demonstrates the potential of crowdsourcing peoples opinions to specific questions over space and time both statistically and geographically, such work potentially allows one to crowdsource peoples perceptions on: fear of household burglary, quality of local schools, who would you vote for? etc. Additionally it is the ability to access real time information and use it for a purpose. For example, with the growth in mobile phones with built in GPS (such as the iPhone) if one had enough participants one could use the data for calibrating pedestrian or traffic simulations and therefore help potentially understand human behavoir. Such as peoples daily movement patterns (see urbanTick for such work).
1.1. GMap Creator
2: Near Real-Time Spatial Surveys
2.1. Mapping the Credit Crunch
2.2. Anti-Social Behaviour in East Anglia
Anti-Social Behaviour in East Anglia.
2.3. The Manchester Congestion Charge
The Manchester Congestion Charge.
3. Geodemographic Profiles of Respondents
However, the geodemographics of the respondents shows there is an inherit bias in who is answering the questions and there is the question to whether or not respondents are influenced by the maps before answering the questions. Further work is to explore how the maps evolve over time, as each response is time stamped and how this relates to news headlines. Additionally, we are currently exploring the geodemographic profiles of each survey in more detail. We have currently re-run the credit crunch with the BBC with slightly different options to the answer.
The question remains the same - "what single factor is hurting you most about the credit crunch?" But we decided to change the categories slightly:Mortgage or rent, Petrol, Food prices, Job security, Utility bills, or Not affected. This survey ran between 5th October 2008 and 3 February 2009 and has now closed. The final map can be viewed here. During this time we received 20,072 responses, which can be broken down as follows (Figure 8): Mortgage or Rent 11.05%, Petrol 4.7%, Food Prices 11.89%, Job Security 27.25%, Utility Bills 21.92%, and Not Affected 23.20%
Gibin M, Singleton AD, Mateos P, and Longley PA. (2008) Exploratory cartographic visualisation of London using the Google Maps API Applied Spatial Analysis and Policy 1(2) pp85-97.
Hudson-Smith A, Crooks AT, Gibin M, Milton R, and Batty M (under review) Neogeography and Web 2.0: Concepts, Tools and Applications, Journal of Location Based Services.
Longley PA, Webber R, Li C, (2008) The UK geography of the e-society: a national classification Environment and Planning A 40(2) pp362-382.
Milton R (2008) GMap Creator, OpenLayers and OpenStreetMap CASA Blog. Available at http://blog.casa.ucl.ac.uk/?p=60 .