A Brief Journey through Foursquare User Check-ins in Cardiff

627b1a10da6bd579fd7f2ea8c73774b8?s=47 Matt J Williams
April 06, 2011
25

A Brief Journey through Foursquare User Check-ins in Cardiff

Informal talk.
Venue: FTS Seminar, Cardiff University School of Computer Science & Informatics.

627b1a10da6bd579fd7f2ea8c73774b8?s=128

Matt J Williams

April 06, 2011
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Transcript

  1. A brief journey through Foursquare user check-ins in Cardiff FTS

    6/April/2011 Matt Williams (joint project with Martin Chorley)
  2. Talk overview 1. Foursquare 2. Data collection 3. Results &

    visualisation 4. Tools
  3. Foursquare • A “location-based online social network” • Founded in

    2007 in New York • Users ‘check-in’ to their current venue • Venues are user-contributed • ‘Mayorship’ of a venue given to the user who has visited the most in two months • Points awarded for checking in
  4. World Foursquare usage Text http://blog.foursquare.com/2011/01/24/2010infographic/

  5. Why use Foursquare? • To meet up with friends? •

    For deals at your favourite venues? • ‘Life-logging’? • Embedded social gaming?
  6. Why use Foursquare? • Answer: Science! • A rich dataset:

    • Human mobility • Geocoded venues • Social graph
  7. Collection method • Problem: user check-in histories are not public

    (understandably!) • ...however, venues do have a “currently here” list that users can opt-in to publicly appear on • Solution: 1. collect a set of venues 2. monitor the venues in real time!
  8. Data collection • Collected 4,314 venues in a 9km x

    7km region • Restricted monitoring to about 2,000 venues • Began monitoring on Monday 21st March
  9. Dataset summary • Collected Mon 21st March - Sat 2nd

    April (13 days) • 3,394 check-ins • 767 venues visited • 4.4 check-ins per venue • 716 users with check-ins • Friends per user: average 126, median 19
  10. When do people check in?

  11. Check-ins over time

  12. How does the popularity of venues vary?

  13. Top 20 venues

  14. Venue popularity linear-linear plot

  15. Venue popularity log-log plot

  16. Where in Cardiff do check-ins occur?

  17. Check-in heatmap

  18. How does check-in activity vary between users?

  19. Top 20 users

  20. User check-ins

  21. How many friends does a user have?

  22. Friendships

  23. Friendships among Cardiff visitors

  24. [An animation of checkins!]

  25. Tools • Python (important! :)) • matplotlib • Microsoft Excel

    • Processing • Google Earth • ffmpeg • heatmap.py (by jjguy) • www.getlatlon.com
  26. Thanks! Any questions? Twitter & 4sq: @voxmjw