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Virtual Geodemographics Alex D Singleton Paul A Longley Centre for Advanced Spatial Analysis and Department of Geography, University College London
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Virtual Geodemographics

Dec 08, 2014

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Page 1: Virtual Geodemographics

Virtual Geodemographics

Alex D Singleton

Paul A Longley

Centre for Advanced Spatial Analysis and Department of Geography,

University College London

Page 2: Virtual Geodemographics

Real Geodemographics

• “Geomarketing”, “Segmentation”, part of “Business Geographics” or “Geobusiness”

• Models of urban socio-spatial structure– Attach a categorical classification to a neighbourhood

Page 3: Virtual Geodemographics

Person

HomeAddress

“Area”

Classify people by where they live

In the UK Typically Unit Postcode (~15 houses)Census Output Area (~40-125 houses)

Page 4: Virtual Geodemographics

Data – Census + Other

Experian: Mosaic

CACI: Acorn

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Segmentations are created by cluster analysis

Area V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 ...

Area1

Area2

Area3

Area4

Area5

Area6

Area7

Area8

...

Inputs…

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Variable 1

Variable 2

Cluster 1Cluster 2

Cluster 3

Cluster Analysis

Page 8: Virtual Geodemographics

Output of cluster analysis

Area Cluster

Area1 1

Area2 1

Area3 2

Area4 1

Area5 3

Area6 3

Area7 3

Area8 2

...

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Page 10: Virtual Geodemographics

SE6 4XD

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Page 12: Virtual Geodemographics

http://www.flickr.com/groups/areaclassification/

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Virtual Geography (Batty, 1997)

1) place/space: the original domain of geography abstracting place into space using traditional methods

2) cspace: abstractions of space into c(omputer)space, inside computers and their networks

4) cyberplace: the impact of the infrastructure of cyberspace on the infrastructure of traditional place

3) cyberspace: new spaces that emerge from cspace through using computers to communicate

Batty, M. (2007) Virtual Geography. Futures. 29(4-5), 337-352

Real Geodemographics

Page 14: Virtual Geodemographics

• The e-Society• 1990s – Technology Use – “Haves” & “Have-nots”

– Digital Divide

• 2009 things are radically different– Usage & Engagement increasingly more complex

• Created a classification which consisted of 8 Groups & 23 Types. – Links to Postcode.

classification

Page 15: Virtual Geodemographics
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Members of this Group often acquire their competence in the use of information technology at work, since many of them are young people working in junior white collar occupations in modern offices. They are keen to become more expert in the use of new technologies and to use them for new applications. Many spend time browsing the Internet but without necessarily making many transactions. Many members of this Group work in large cities and may be starting a life in a house that they own, typically in one of the cheaper inner suburbs. Their use of the Internet at work may be a practice that their employers may be keen to control or reduce.

Group C : Becoming engaged

classification

Page 17: Virtual Geodemographics

Members of this Group have every confidence in their abilities to undertake on-line transactions and to make full use of electronic technologies. These are the types of people who are able to make use of personalisation and configuration options. They enjoy exploring the features in electronic menus and will navigate them in an efficient manner. They prefer on line to inter-personal sources of information and make use of the Internet as an information source for obtaining best value for money. These people are heavy email users. Many of them are involved in the development of information technology applications at work, and see leisure time spent on electronic technologies as enhancing their human capital.

Group H: e-Experts

classification

Page 18: Virtual Geodemographics

The ‘E – unengaged’ are typically groups that do not have access to electronic communications or technologies. Most are too old, too poor or too poorly educated to be able to access them, and instead traditionally rely upon personal contacts they trust for advice. Within this Group there are low levels of literacy and many people do not feel that their life outcomes are much subject to their own decisions. Within this group there is a very low level of ownership of personal computers, very little access to them at work and low ambition to master the skills to take advantage of information technologies. These people have a very low level of using email at any location or participating in other on-line activities.

Group A : e-Unengaged

classification

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SE6 4XD

Page 21: Virtual Geodemographics

Location Map

Similarity Chart

Pen Portrait

Feedback

Page 22: Virtual Geodemographics
Page 23: Virtual Geodemographics

Death of distance…

• Communication enabled by the Internet would erode the importance of place/space (Caincross, 1997)

• Connection to the Internet has not replaced our interactions and organisation across real space– more so for some than others (eSociety)

• However the Internet is changing

– the early Web was primarily one-directional, allowing a large number of users to view the contents of a comparatively small number of sites, [whereas] the new Web 2.0 is a bi-directional collaboration in which users are able to interact with and provide information to central sites, and to see that information collated and made available to others’

Goodchild (2007)

Page 24: Virtual Geodemographics

Virtual Geography (Batty, 1997)

1) place/space: the original domain of geography abstracting place into space using traditional methods

2) cspace: abstractions of space into c(omputer)space, inside computers and their networks

4) cyberplace: the impact of the infrastructure of cyberspace on the infrastructure of traditional place

3) cyberspace: new spaces that emerge from cspace through using computers to communicate

Batty, M. (2007) Virtual Geography. Futures. 29(4-5), 337-352

Real Geodemographics

eSociety Classification

Page 25: Virtual Geodemographics

Evidence of Cyberplace: Virtual Money

Virtual Economies Linden $

Second Life – Linden Labs

Page 26: Virtual Geodemographics

Evidence of Cyberplace: Information Asymmetry

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Evidence of Cyberplace: Social GPS

http://www.loopt.com/phones/iphone

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Evidence of Cyberplace: Store Cards

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Resources of Cyberplace: Rich Data / Mining

http://smalltalkapp.com

Page 30: Virtual Geodemographics

Resources of Cyberplace: Rich Data / Mining

http://senseable.mit.edu/

Page 31: Virtual Geodemographics

Problems for models which attempt to incorporate Cyberspace behaviours

• What are the units?– Individuals? Areas?

• What are the data?– How can these be linked?

• “Near” is not necessarily “near””– Cyberspaces are scale free

• Digital footprints (data transfer & activities)• Parallels to offline data disclosure

Page 32: Virtual Geodemographics

Virtual Geodemographics

• How do you start to look at some of these problems?

Page 33: Virtual Geodemographics

friendnames

friendnames.publicprofiler.org

Coming Soon!