10 urban intangible properties
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10 urban intangible properties
- 1. Quantifying 10 intangible urban properties daniele.quercia@ – Social Dynamics team, Cambridge UK
- 3. Quantify intangible properties AI for Human Systems
- 4. What’s in it for you? daniele.quercia@ – Social Dynamics team, Cambridge UK 1. engagement 2. urban vitality 3. walkability 4. urban beauty 5. sensory perceptions 6. social relationships 7. ambiance 8. indoor activities 9 city’s pulse (nokia health) 10. city’s eating habits (& disorders)
- 5. intangible property 1= engagement
- 6. [cscw 2018] Community Engagement Triage: Lightweight Prompts for Systematic Reviews Are you failing to engage colleagues and peers in a complex project?Would you like to open a new community and don’t know why? Play with a tinder-like engagement game, build your own rules of engagement step by step, and download them in the form of a beautiful stack of cards. goodcitylife.org/six-hacks/
- 7. [cscw 2018] Community Engagement Triage: Lightweight Prompts for Systematic Reviews
- 8. [cscw 2018] Community Engagement Triage: Lightweight Prompts for Systematic Reviews
- 9. Play online on www.goodcitylife.org/six-hacks Print & play cards (pdf) [cscw 2018] Community Engagement Triage: Lightweight Prompts for Systematic Reviews
- 10. intangible property 2= urban vitality
- 11. The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective
- 12. The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective
- 13. Urban diversity to urban vitality 24 CONCENTRATION LAND USE SMALL BLOCKS VACUUMS CLOSENESS TO HIGHWAYS CLOSENESS TO SMALL PARKS X CLOSENESS TO HIGHWAYS EMPLOYMENT DENSITY HOUSING TYPES INTERSECTIONS DENSITY 3rd PLACESX CLOSENESS TO HIGHWAYS Predict URBAN VITALITY Z [ :0.77 URBAN DIVERSITY CONDITIONS URBAN INDEXES The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective
- 14. intangible property 3= walkability
- 15. The Digital Life of Walkable StreetsWHY WALKABILITY? house prices, health, carbon saving (light-bulbs 1 year= living in a walkable for 1 week) In an urbanized future, how will cities provide the best quality of life? By being safe and sustainable
- 16. “The General Theory of Walkability”
- 17. All Flickr picture tags in London (public API ~ 1B tags) Digital footprints distinguish walkable streets from un- walkable ones
- 18. 0.49 −0.78 0.89 −0.5 0.0 0.5 car (ci) walkability (wi) z−walkability tag category r(walkability,tagpresence)
- 19. 0.49 −0.78 0.89 −0.5 0.0 0.5 car (ci) walkability (wi) z−walkability tag category r(walkability,tagpresence)
- 20. r(safe,night)= 0.60 safe street tend to be visited at night as well
- 21. Distinguishing walkable streets vs. unwalkable ones: mainly in terms of upload time and tagging * * limited data vs. high penetration
- 23. intangible property 4= urban beauty
- 24. A B [ACM cscw’14] Aesthetic Capital: What Makes London Look Beautiful, Quiet, and Happy? goodcitylife.org/happymaps
- 25. [ACM cscw’14] Aesthetic Capital: What Makes London Look Beautiful, Quiet, and Happy? goodcitylife.org/happymaps
- 27. - cars - isolated buildings Social capital Happy city + public gardens + small streets [ACM cscw’14] Aesthetic Capital: What Makes London Look Beautiful, Quiet, and Happy? goodcitylife.org/happymaps
- 28. [ACM HT14] The shortest path to happiness
- 30. FaceLift: A transparent deep learning framework recreating the urban spaces people intuitively love
- 31. FaceLift: A transparent deep learning framework recreating the urban spaces people intuitively love
- 36. Original Template Transform Beautified transformation FaceLift: A transparent deep learning framework recreating the urban spaces people intuitively love
- 37. FaceLift: A transparent deep learning framework recreating the urban spaces people intuitively love
- 40. facelift | beautifying the world
- 41. FaceLift User interfaceSystemConcept A transparent generative deep learning model to beautify the world Paper and demo
- 42. FaceLift User interfaceSystemConcept A transparent generative deep learning model to beautify the world Paper and demo
- 43. FaceLift User interfaceSystemConcept A transparent generative deep learning model to beautify the world Paper and demo
- 44. intangible property 5= sensory perceptions
- 45. Sensory Mapping [AAAI ICWSM] Smelly Maps: The Digital Life of Urban Smellscapes [AAAI ICWSM] The Emotional and Chromatic Layers of Urban Smells
- 46. smell walks Amsterdam, Pamplona, Glasgow, Edinburgh, Newport, Paris, New York.[AAAI ICWSM] Smelly Maps: The Digital Life of Urban Smellscapes [AAAI ICWSM] The Emotional and Chromatic Layers of Urban Smells
- 47. Match collected words to social media London & Barcelona 17M 436K 1.7M
- 48. URBAN SMELLSCAPE AROMA WHEEL
- 49. Both positive and negative smells
- 51. [AAAI ICWSM] Smelly Maps: The Digital Life of Urban Smellscapes [AAAI ICWSM] The Emotional and Chromatic Layers of Urban Smells
- 52. Chatty Maps [Royal Society] Chatty Maps: Constructing sound maps of urban areas from social media data goodcitylife.org/chattymaps
- 54. intangible property 6= social relationships
- 55. High-level concepts from conversational text Model social interactions as people perceive them Coloring in the Links: Capturing Social Ties as They are Perceived
- 56. Crowd perception of relationships Similarity, romance, social support, trust, identity, respect, knowledge transfer, power, fun, conflict Coloring in the Links: Capturing Social Ties as They are Perceived
- 57. <Document ID: change ID in footer or remove> <Change information classification in footer>
- 58. <Document ID: change ID in footer or remove> <Change information classification in footer>
- 59. <Document ID: change ID in footer or remove> <Change information classification in footer>
- 60. intangible property 7= ambiance
- 63. Ambiance Image Dataset Data Collection • From Flickr geotagged pictures • Match images tags with taxonomy
- 64. Posit ive N egat ive Posit ive N egat ive B eaut iful Cr eat ive Cozy Cosm op olit an L ively M oder n St ylish Joyful A lt er nat ive Quiet Fancy U nique Popular Figure 2: Most and least lively wards in mopolitan (it comprisesNotting Hill, wher Community lives). The Borough of the the financial heart of the city: definitely c ambiance), less obviously Alternative (se nent ambiance); we can explain the fac emerging as Alternative by looking at th protest/ demonstration events in London, Examples
- 66. intangible property 8= indoor activities
- 67. indoor position on map + indoor image= image of indoor space
- 71. Fig 10. Maps of activity diversity D at each LSOA in London.
- 72. Fig 11. Maps of activity diversity D at each census tract in New York city.
- 75. Existing Image Anonymisation Techniques Car Plates Faces
- 76. What about private spaces? A Whole in Literature Part of the personal sphere. Rich of privacy-sensitive elements which can suggest the owner’s identity
- 77. General Idea Generalisable techniques for image anoymisation +Anonymisation Utility Class = Bedroom Sentiment = Neutra Security Owner = Mary Utility Class = Bedroom Sentiment = Neutral Security Owner = ??
- 78. intangible property 9= city’s pulse (perceptions of the ext world from nokia health)
- 79. NOKIA HEALTH • 11,600 users in London and San Francisco over 365 days • ~4M daily datapoints • Steps, sleep duration, heart rate
- 80. Steps By looking at volume alone isn’t that bad
- 81. Sleep By looking at volume alone isn’t that bad
- 82. Heart rate By looking at volume alone isn’t that bad
- 83. Unique proposition Two new metrics to measure biorhythms
- 87. intangible property 10= city’s eating habits (& disorders)
- 88. FOOD CONSUMPTION • 1.6M customer in London over 365 days • ~1.6B food purchases in 400+ stores • Products =nutrients
- 89. consumption of food =? prevalence of diseases At city scale…
- 90. Londoners deviates from recommended WHO limits
- 91. Map of Nutrient Diversity
- 92. You can predict diabetes from nutrient diversity & calories, for example 𝐷𝑖𝑎𝑏𝑒𝑡𝑒𝑠 = 𝛼 + 𝛽1 𝐶𝑎𝑙𝑜𝑟𝑖𝑒𝑠 + 𝛽2 𝐷𝑖𝑣𝑒𝑟𝑠𝑖𝑡𝑦 → 𝑅2 = 0.51,Diabetes Diabetes
- 93. What’s in it for you? daniele.quercia@ – Social Dynamics team, Cambridge UK 1. engagement 2. urban vitality 3. walkability 4. urban beauty 5. sensory perceptions 6. social relationships 7. city’s pulse (perceptions of the ext world from Nokia Health) 8. ambiance 9. indoor activities 10. city’s eating habits (& disorders)