from geographic location to network location: the potential of big social data
TRANSCRIPT
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From Geographic Location to Network Location: The Potential of Big Social DataProf. Axel BrunsARC Future FellowDigital Media Research CentreQueensland University of TechnologyBrisbane, [email protected] – @snurb_dot_info – http://mappingonlinepublics.net/
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BIG DATA
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BIG SOCIAL DATA
(http://siliconangle.com/blog/2011/08/09/twitter-unravel-the-mysteries-of-big-data/)
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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)
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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)
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BIG SOCIAL GEODATA?
http://users.humboldt.edu/mstephens/hate/hate_map.html
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GEOTAGGING IS UNCOMMON
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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%)
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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
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Education
Agriculture
Literature
Adelaide / SA
FoodWine
Beer
Parenting
Mums PR
Netizens
Marketing
InvestingReal Estate
Home BusinessSole Traders
Self-Help
HR / Support
Followback
Urban MediaUtilities
Advertising
Business
Fashion
Beauty
ArtsCinema
Journalists
Politics
Hard RightLeftists
News
CyclingTalkback
Music
TVV8s UFC
NRL
AFL
Football
Horse Racing
CricketNRU
Celebrities
Hillsong
Perth
PopMedia
Teen Idols
Cody Simpson
THE AUSTRALIAN TWITTERSPHERE
~140k Australian accounts with degree > 1000, as of Sep. 2013 (of a total 2.8m accounts found)
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ACCOUNTS CREATED IN 2006
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ACCOUNTS CREATED IN 2007
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ACCOUNTS CREATED IN 2008
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ACCOUNTS CREATED IN 2009
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ACCOUNTS CREATED IN 2010
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ACCOUNTS CREATED IN 2011
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ACCOUNTS CREATED IN 2012
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ACCOUNTS CREATED IN 2013
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AFL GRAND FINAL
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Q&A
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BACK TO GEOLOCATION?
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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?
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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
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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.