Geographic data mining of online social networks

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    Geographic data mining of online social networks - Presentation Transcript

    1. GEOGRAPHIC DATA MINING OF ONLINE SOCIAL NETWORKS Alex D Singleton Department of Geography and Centre for Advance Spatial Analysis , University College London
    2. SOCIAL NETWORKS Method of expressing the social environment as “patterns of • regularity among interacting units” (Wasserman, 1994) Social actors range in scale and form - individuals, areas, companies ... • Relational data - link actors together •
    3. Crossley, 2009: Post Punk, Manchester
    4. Connections by Non-Executive Directors Tampubolon, 2006: FTSE 100 Executives
    5. ARTICLE IN PRESS 621 J.L. Wylie et al. / Health & Place 13 (2007) 617–628 Fig. 1. Illustration of the hotel network as generated by Pajek. Hotels are indicated with square symbols; people with circle symbols. Each line connects an IDU with a specific hotel, as named by them as a site where they had injected drugs in the past 6 months. The hotels numbered 1–11 are the 11 hotels identified as 3-core. 3-core IDU are indicated by K; 2-core IDU as ; and 1-core IDU as J. Wylie, 2006: Injection Drug Use and Geographic Setting (Hotels)
    6. LANGUAGE OF SN Node (Vertices) Lines (Edges)
    7. LANGUAGE OF SN Node (Vertices) Lines (Edges) Binary (1,0) Continuous Integer Directional (+,-)
    8. SN AND SOCIAL CAPITAL “features of social life - networks, norms and trust - that enable • participants to act together more effectively to pursue shared objectives” (Putnam, 1995:664) Individual V Group or Area • How does this translate online? •
    9. SOCIAL NETWORK ONLINE Facebook (www.facebook.com) • May 2008 - 123.9 million unique users (McCarthy, 2008) • API released 2006 - 650,000 developers world wide •
    10. Clusters - Based on friend links What about node characteristics? Touchgraph
    11. NAMES DATA June 2006 • GB surnames search • Ethnicity statistics • Social status • Experian Mosaic •
    12. NAME SOCIAL STATUS Modified electoral roll • Address Level (postcode) • Geodemographic - Acorn, CACI • 5 Categories, 17 Groups, 56 Types • Rank Types by wealth •
    13. NAME SOCIAL STATUS Append wealth rank to forename and surname by postcode • Create median, and standard deviation rank for each name, rank • name by median, then lowest standard deviation where ties Person scores created by joining forename and surname scores • Name ranks used to create a measure at OA •
    14. NAME SOCIAL STATUS Append wealth rank to forename and surnameun! postcode by • rf fo st for each name, rank u • Create median, and standard deviation jrank c - deviation where ties tifi name by median, then lowest standard ien sc y rjoining forename and surname scores • Person scores created ve by ot sn s i to create a measure at OA • Name ranks hiused T
    15. Jeremy Paxman 99 Judi Dench 94 Sebastian Coe 88 Christian Bale 78 Nigella Lawson 74 Cli Richard 69 Rio Ferdinand 62 Elton John 57 Robert Carlyle 52 Robbie Williams 49 David Beckham 42 Martine McCutcheon 39 John Lennon 33 Terry Christian 30 Jim Carrey 23 Britney Spears 17 Coleen McLoughlin 7 Wayne Rooney 5
    16. Client Browser API PHP UCL Server MYSQL
    17. MYNAMEPROFILER http://apps.facebook.com/mynameprofiler • You Friends Ranked Friends Area
    18. P User Install
    19. P User Install Friends
    20. P User Install Friends Friends of Friends
    21. P User Install
    22. P P P User Install
    23. P P P P P P P P P User Install P P
    24. • Howdo virtual connections map onto real world locations? • Places, geodemographics © Crown copyright 1999 • How are virtual connections created by real world associations? • Edge V Node characteristics • What do these associations tell us about social capital? 0 50 100 km
    25. NEXT STEPS Launch of the site - probably press release to BBC • Data • Modified community detection algorithm: examine both edges and • nodes Examine the geodemographic profiles of those clusters which are • identified
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