Psychological Maps 2.0 [www 2013]
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Psychological Maps 2.0 [www 2013]
- 1. Psychological Maps 2.0: A web engagement enterprise starting in London
- 3. Situation 75% in USA (already!)
- 4. Situation plus 1.2B by 2025 in USA
- 5. Situation plus 5M /month in developing c.
- 9. Solution $ Timely allocation of scarce resources
- 10. census deprivation + londoners on twitter
- 11. r=.350 word count r=.365 MaxEnt [cscw’12] Tracking Gross Community Happiness from Tweets
- 12. social media environment sports health Royal wedding Spanish/Portuguese celebrity gossips Talk of the City [ICWSM’12]
- 13. Twitter |o|
- 22. draw a map
- 27. WEIRD trap! Few hundreds of WEIRDos White,Educated,Industrialized,Rich, and Democratic undergraduates
- 28. WWW Game!
- 30. URBANOPTICON.ORG
- 31. “I’ve been living in London for the past 35 years and I felt like a tourist. There were so many places I had no clue where they were. It is frustrating to get a score of 200 [out of 1000]! ”
- 33. launched few months ago > 2K players
- 34. “Yesterday we had few friends over for dinner. I started to play the game on my laptop, and that escalated into a ridiculous competition among all of us that left my husband (the only Londoner in the room) quite injured, so to speak ”
- 35. Demographics age&gender ~ Underground passengers != Facebook/Twitter users
- 36. Regions
- 37. Regions
- 38. Boroughs
- 39. Boroughs
- 40. Londoners vs. UK vs. World
- 42. Visibility & Social Deprivation
- 44. Distinctiveness (e.g., interesting architecture) Area more visibile than exposure would suggest
- 46. info value of pix?
- 47. pic info = quantitative “fuzzy” concepts
- 49. (a) (b) (c) (d) (e) (f) (g) (h) Figure 5: Visual Wordsfor Beauty (top row) and Ugly (bottom row). and guardrails. The red dots on top-ranked pictures hose on bottom-ranked ones mean two different things ormer reflect positive(e.g., happy) visual words, while Picture Quality Bias. Photos might not necessarily what they aresupposed to show (representativeurban s in each neighborhood), and somepictures might beof
- 50. only london?
Notas do Editor
- 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 flow so 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.
- in particular, transport analysts and planners need to be able to understand and predict passenger flow so 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.
- in particular, transport analysts and planners need to be able to understand and predict passenger flow so 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.
- in particular, transport analysts and planners need to be able to understand and predict passenger flow so 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.
- in particular, transport analysts and planners need to be able to understand and predict passenger flow so 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.
- in particular, transport analysts and planners need to be able to understand and predict passenger flow so 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.