Exploring the Global Demographics of TwitterAxel Bruns, Darryl Woodford, and Troy Sadkowsky

ARC Centre of Excellence for Creative Industries and Innovation

Queensland University of Technology

Brisbane, Australia

a.bruns / dp.woodford / t.sadkowsky @ qut.edu.au

@snurb_dot_info / @dpwoodford / @tsadkowsky

http://socialmedia.qut.edu.au/ / http://mappingonlinepublics.net/

THE GLOBAL TWITTER USERBASE

• Limited information:– Some details from Twitter in IPO documents and updates to shareholders– Some commercial research (e.g. Socialbakers), using unknown methods– Some extrapolations based on surveys, usually country-specific (e.g. Pew

Centre, Sensis)

• Significant gap:– Difficult to assess global and national Twitter patterns without background data– Impossible to assess relative size of local Twitterspheres without global data

OUR APPROACH

• Data gathering and analysis:– Slow crawl through Twitter account ID numberspace, from ID 0 to ID ~2,000,000,000

(as of 31 Aug. 2013)– Retrieval of all publicly available profile information for each ID from Twitter API– Storage and processing in Google BigQuery database– Data analysis via Tableau Desktop

• Limitations:– Accounts, not users (!)– All dates in AEST– Single snapshot, blurry edges: accounts created/deleted during data gathering– Twitter API not always a completely reliable data source– Data for most recent accounts will have changed substantially since gathering– No information available about deleted historical accounts– Privacy concerns (rightly) prevent any detailed profiling

CUMULATIVE GROWTH

DAILY GROWTH

TWITTER AND BREAKING NEWS

ACCELERATING GROWTH?

• Oldest surviving accounts:– @jack (ID #12), @biz (ID #13): 22 March 2006

• Daily growth:– From ~200k (March 2009) to ~900k (August 2013)

• Monthly growth:– From ~5m (March 2009) to ~26m (August 2013)

• But:– Dataset only includes accounts which still exist:

growth = accession – attrition– Attrition is likely to increase with time: most recent accounts least likely to be

deleted soon

DISTRIBUTION OF TWEETING ACTIVITY

FOLLOWERS / FRIENDS DISTRIBUTION

FRIENDS:FOLLOWERSF

oll

ow

ers

Friends

FRIENDS:FOLLOWERScolour = average account age

FRIENDS:FOLLOWERS (DETAIL)colour = average account age

1:1

0.9:1

INCREASINGLY PUBLIC

Protected accounts

PU

BL

IC V

S.

PR

IVA

TE

INCREASINGLY GLOBALIN

TE

RF

AC

E L

AN

GU

AG

E

INCREASINGLY GLOBAL

Languages / timezones / geo

INT

ER

FA

CE

TIM

EZ

ON

E

INCREASINGLY LIKE FACEBOOK?

http://mappingonlinepublics.net/@snurb_dot_info

@dpwoodford

@tsadkowsky

@jeanburgess

@timhighfield

@socialmediaQUT – http://socialmedia.qut.edu.au/

This research is funded by the Australian Research Council through Future Fellowship and LIEF grants FT130100703 and LE140100148.