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# Finger on the Pulse: Towards a Real-time City Health Monitor

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• explain titleshould have included a subtitle
• we use the gravity model to study flows of passengers on London’s rail system.extensive network. 588 stations. click for oyster card.oyster cards record the point and time of entry… and link all journeys to a user id, so we can analyse individual travel patterns.stats – 1 month = 77 million journeys by 5 million users between 588 stations.
• we use the gravity model to study flows of passengers on London’s rail system.extensive network. 588 stations. click for oyster card.oyster cards record the point and time of entry… and link all journeys to a user id, so we can analyse individual travel patterns.stats – 1 month = 77 million journeys by 5 million users between 588 stations.
• we use the gravity model to study flows of passengers on London’s rail system.extensive network. 588 stations. click for oyster card.oyster cards record the point and time of entry… and link all journeys to a user id, so we can analyse individual travel patterns.stats – 1 month = 77 million journeys by 5 million users between 588 stations.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• [describe diagram] in analogy with Newton’s…click for equation[describe equation] k, alpha, beta, gamma are normally fitted to the particular system being modeled----- Meeting Notes (13/06/2012 16:31) -----add symobols to picture
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• Our proposal is to use AFC data in order to build a well established form of interaction model – the gravity model – to describe the flow of passengers on public transport systems.introduced by Zipf in 1946 – successfully used to help explain flow of humans, goods, information and disease, at inter-city level and above.
• we use the gravity model to study flows of passengers on London’s rail system.extensive network. 588 stations. click for oyster card.oyster cards record the point and time of entry… and link all journeys to a user id, so we can analyse individual travel patterns.stats – 1 month = 77 million journeys by 5 million users between 588 stations.
• the world is currently undergoing a massive influx of people into cities.which means that (next slide)
• the world is currently undergoing a massive influx of people into cities.which means that (next slide)
• the world is currently undergoing a massive influx of people into cities.which means that (next slide)
• in particular, transport analysts and planners need to be able to understand and predict passenger flowso far there has been little work on modeling flows on public transport systems in an urban environment, or at the intra-city level.one reason for this may be lack of data, but with adoption of AFC in cities all over the world, this data is now readily available.
• explain titleshould have included a subtitle
• ### Finger on the Pulse: Towards a Real-time City Health Monitor

1. 1. FINGER ON THE PULSEMonitoring Health of the CityChris Smith, Daniele Quercia, Licia Capra
2. 2. offline & online
3. 3. census deprivation + data
4. 4. census deprivation + londoners on twitter
5. 5. census deprivation + sentiment
6. 6. predicting socioeconomic well-being with twitter r=.350 word count r=.365 MaxEnt
7. 7. census deprivation + topics
8. 8. Talk of the City [ICWSM’12] social media environment sports health Royal wedding Spanish/Portuguese celebrity gossips
9. 9. census deprivation + tube trips
10. 10. Proposal
11. 11. Proposal
12. 12. ProposalDeprivation might be connected to: HP1: “unexpected” mobility HP2: use of bus (compared to tube use) HP3: low social/geographic diversity
13. 13. Hypothesis 1build a gravity model ~ flow of passengers
14. 14. What is a gravity model? a b Pi PjTij = k g dij Pj Pi dij
15. 15. Hypothesis 1gravity works: r= .72!
16. 16. Hypothesis 1Where the model fails to fit wellunexplained bit: prevailing socioeconomic factors ?
17. 17. Hypothesis 1Where the model fails to fit wellunexplained bit: prevailing socioeconomic factors ?We look at (gravity)Residuals
18. 18. Hypothesis 2#tube passengers proportional to population“Bus/Car bias”: residual between #passengers and population
19. 19. Hypothesis 3Social/Geographic diversity: socio-economic advantage“Social/Geo” diversity
20. 20. Hypothesis 1+2+3 Gravity Residuals *** Bus Bias ** Socio/Geo Diversity n.s.s. R^2= 9% IMD R^2= 34% Living Environment
21. 21. Hypothesis 1+2+3 (top+bottom only) Gravity Residuals *** Bus Bias ** Socio/Geo Diversity n.s.s. R^2= 27% IMD R^2= 54% Living Environment
22. 22. Predicting…
23. 23. Predicting…
24. 24. Predicting…
25. 25. So what?Strong Passenger flow–urban deprivation(timely & effective & longitudinal)
26. 26. Situation  (Its already 75% in the USA)
27. 27. Situation By 2025 another 1.2 billion living in urban areas
28. 28. Situation Cities in developing countries: 5M new inhabitants each month
29. 29. Problem Inequality! Timely allocation of scarce resources
30. 30. census deprivation + “mental maps”
31. 31. draw a map
32. 32. launched few months ago & > 2K players
33. 33. Visibility & Social Deprivation
34. 34. FINGER ON THE PULSEMonitoring Health in the CityChris Smith, Daniele Quercia, Licia Capra