An unobtrusive behavioral model of "gross national happiness"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Tracking "gross community happiness" from tweets
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
The hidden image of the city: sensing community well-being from urban mobility
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Urban: crowdsourcing for the good of London
Proceedings of the 22nd international conference on World Wide Web companion
Psychological maps 2.0: a web engagement enterprise starting in London
Proceedings of the 22nd international conference on World Wide Web
Creating smart information services for tourists by means of dynamic open data
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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A common metaphor to describe the movement of people within a city is that of blood flowing through the veins of a living organism. We often speak of the 'pulse of the city' when referring to flow patterns we observe. Here we extend this metaphor by hypothesising that by monitoring the flow of people through a city we can assess the city's health, as a nurse takes a patient's heart-rate and blood pressure during a routine health check. Using an automated fare collection dataset of journeys made on the London rail system, we build a classification model that identifies areas of high deprivation as measured by the Indices of Multiple Deprivation, and achieve a precision, sensitivity and specificity of 0.805, 0.733 and 0.810, respectively. We conclude with a discussion of the potential benefits this work provides to city planning, policymaking, and citizen engagement initiatives.