from geographic location to network location: the potential of big social data

From Geographic Location to Network Location: The Potential of Big Social DataProf. Axel BrunsARC Future FellowDigital Media Research CentreQueensland University of TechnologyBrisbane, Australiaa.bruns@qut.edu.au – @snurb_dot_info – http://mappingonlinepublics.net/

BIG DATA

BIG SOCIAL DATA

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

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)

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)

BIG SOCIAL GEODATA?

http://users.humboldt.edu/mstephens/hate/hate_map.html

GEOTAGGING IS UNCOMMON

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%)

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

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)

ACCOUNTS CREATED IN 2006

ACCOUNTS CREATED IN 2007

ACCOUNTS CREATED IN 2008

ACCOUNTS CREATED IN 2009

ACCOUNTS CREATED IN 2010

ACCOUNTS CREATED IN 2011

ACCOUNTS CREATED IN 2012

ACCOUNTS CREATED IN 2013

AFL GRAND FINAL

Q&A

BACK TO GEOLOCATION?

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?

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

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.