Invited presentation at the Pivotal 2015 International Executive Summit, Brisbane, 30 June 2015.

1. From Geographic Location
to Network Location:
The Potential of Big Social Data
Prof. Axel Bruns
ARC Future Fellow
Digital Media Research Centre
Queensland University of Technology
Brisbane, Australia
a.bruns@qut.edu.au – @snurb_dot_info – http://mappingonlinepublics.net/

2. BIG DATA

3. BIG SOCIAL DATA
(http://siliconangle.com/blog/2011/08/09/twitter-unravel-the-mysteries-of-big-data/)

4. BIG SOCIAL GEODATA?
Twitter Decahose English-language georeferenced tweets 23 October 2012 to 30 November
2012. (Leetaru et al., 2013 – http://firstmonday.org/article/view/4366/3654)

5. BIG SOCIAL GEODATA?
Network map showing locations of users retweeting other users (geocoded Twitter Decahose tweets 23
October 2012 to 30 November 2012) .(Leetaru et al., 2013 – http://firstmonday.org/article/view/4366/3654)

6. BIG SOCIAL GEODATA?
http://users.humboldt.edu/mstephens/hate/hate_map.html

7. GEOTAGGING IS UNCOMMON

8. GEOLOCATION? NETWORK LOCATION!
• Account information available from Twitter API:
– Description (free text)
– Location (free text)
– Follower network
– Twitter join date
– Interface language
– Interface timezone
– Key stats (# followers, followees, tweets, etc.)
• Limitation:
– Not available for ‘protected’ accounts (~3.5%)

9. MAPPING A NATIONAL TWITTERSPHERE
• Account information selected:
– Description: mentions of Australian terms, top locations
– Location: mentions of Australia, top locations
– Interface timezone: one of eight Australian state timezones

10. Education
Agriculture
Literature
Adelaide / SA
Food
Wine
Beer
Parenting
Mums PR
Netizens
Marketing
Investing
Real Estate
Home Business
Sole Traders
Self-Help
HR / Support
Followback
Urban Media
Utilities
Advertising
Business
Fashion
Beauty
Arts
Cinema
Journalists
Politics
Hard RightLeftists
News
CyclingTalkback
Music
TV
V8s
UFC
NRL
AFL
Football
Horse Racing
Cricket
NRU
Celebrities
Hillsong
Perth
Pop
Media
Teen Idols
Cody Simpson
THE AUSTRALIAN TWITTERSPHERE
~140k Australian accounts with
degree > 1000, as of Sep. 2013
(of a total 2.8m accounts found)

11. ACCOUNTS CREATED IN 2006

12. ACCOUNTS CREATED IN 2007

13. ACCOUNTS CREATED IN 2008

14. ACCOUNTS CREATED IN 2009

15. ACCOUNTS CREATED IN 2010

16. ACCOUNTS CREATED IN 2011

17. ACCOUNTS CREATED IN 2012

18. ACCOUNTS CREATED IN 2013

19. AFL GRAND FINAL

20. Q&A

21. BACK TO GEOLOCATION?

22. NETWORK LOCATION  GEOLOCATION?
• Inferring (typical) geolocation:
– More local following than intercity/state/country following?
 Can we infer your location from that of your followees?
– More discussion of local than non-local issues?
 Can we infer your location from your typical topics?
 Can we infer your location from your network’s topics?
• Combining network and geographic location data:
– How does information travel across the network?
– Does geographic location affect information flows here?

23. LIMITATIONS
• Twitter API policies:
– Pursuit of short-term goals, not long-term strategies
– Ill-conceived push to raise revenue through data sales
– Counterproductive relationship with research community
– Data access shaped to privilege certain limited methods
 Most ‘big data’ Twitter research conducted by Twitter, Inc.
and commercial research institutes

24. http://mappingonlinepublics.net/
@snurb_dot_info
@jeanburgess
@tsadkowsky
@petamitchell
@flxvctr
@socialmediaQUT – http://socialmedia.qut.edu.au/
@qutdmrc – https://www.qut.edu.au/research/dmrc
This research is funded by the Australian Research Council through Future Fellowship and LIEF
grants FT130100703 and LE140100148.