Mapping Social TV Audiences:
The Footprints of Leading Shows
in the Australian Twittersphere
Axel Bruns, Darryl Woodford, Tim Highfield, and Katie Prowd
Social Media Research Group
Queensland University of Technology
Brisbane, Australia
a.bruns / dp.woodford / t.highfield / k2.prowd @ qut.edu.au
@snurb_dot_info / @dpwoodford / @timhighfield / @katieprowd
http://socialmedia.qut.edu.au/

THE AUSTRALIAN TWITTERSPHERE
• Twitter in Australia:
– Strong take-up since 2009
– Centred around 25-55 age range, urban, educated, affluent users (but gradually broadening)
– Significant role in crisis communication, political communication, audience engagement, …
• Mapping the Twittersphere:
– Long-term project to identify all Australian Twitter accounts
– First iteration: snowball crawl of follower/followee networks
• Starting with key hashtag populations (#auspol, #spill, …)
• Map of ~1m accounts in early 2012
– Second iteration: full crawl of global Twitter ID numberspace through to Sep. 2013
(~870m accounts)
• Filtering by description, location, timezone fields
• Focus on identifiably Australian cities, states, timezones and other markers
• 2.8 million Australian accounts identified (by Sep. 2013)
• Retrieval of their follower/followee lists

MAPPING TELEVISION FOOTPRINTS
• Mapping the Twittersphere:
– Filtered to include only accounts with (followers + followees) >= 1000
• 140k accounts, 22.8m follower/followee connections within this group
– Mapped using Gephi Force Atlas 2 algorithm (LinLog mode, scaling 0.0001, gravity 0.5)
– Qualitative interpretation of network clusters based on high-degree nodes in each cluster
• Determining television footprints:
– Data gathered on selected hashtags / keywords for a range of key TV events
– Data filtered for participating accounts included in the 140k most connected users
– Data superimposed on underlying network map
• Applications:
– Audience engagement analytics beyond mere volumetrics
– Better assessment of show reach: breadth, depth, thematic fit of audience engagement
– Comparative benchmarking across shows

TELEVISION SHOWS SELECTED
• Shows included:
– 60 Minutes (Australian edition): news magazine, Nine Network – #60Mins, #ExtraMinutes, @60Mins
– Q&A: political talkshow, Australian Broadcasting Corporation – #qanda, qanda
– The Project: news talk panel, Network Ten – #theprojecttv, @theprojecttv, theprojecttv
– Big Brother: reality TV, Nine Network – #BBAU, #BBAU9, @BBAU9, #bigbrotherau
(all tracked between 3 Sep. and 7 Oct. 2014)
– AFL Grand Final: Seven Network – #AFLGF, AFL, HAWvSYD, …
(27 Sep. 2014, tweets tracked since 26 Sep. 2014)
– NRL Grand Final: Nine Network – #NRLGF, NRL, …
(5 Oct. 2014, tweets tracked since 3 Oct. 2014)
– FFA Cup: FOXTEL – #FFACup, @FFACup, FFACup, …
(major rounds 29 July to 16 Dec. 2014, tweets tracked since 29 July 2014)
– Commonwealth Games: Network Ten – #Glasgow2014, #CWG2014, …
(23 July to 3 Aug. 2014, tweets tracked since 30 June 2014)
– Tour de France: SBS – #letour, #tdf, #sbstdf
(5-27 July 2014, tweets tracked since 30 June 2014)

Education
Agriculture
Literature
Adelaide / SA
Food
Wine
Beer
Leftists Hard Right
Netizens
Politics
Journalists
Marketing
Mums PR
Parenting
Real Estate
Investing
Home Business
Sole Traders
Self-Help
HR / Support
NRL
Followback
Urban Media
Utilities
Advertising
Business
TV
Fashion
Beauty
Arts
Cinema
News
TalkbackCycling
Music
V8s
UFC
AFL
Football
Horse Racing
Cricket
NRU
Celebrities
Hillsong
Perth
Pop
Media
Teen Idols
Cody Simpson
THE AUSTRALIAN TWITTERSPHERE

60 MINUTES

Q&A

THE PROJECT

BIG BROTHER

AUDIENCE OVERLAP: POLITICS

AFL GRAND FINAL

NRL GRAND FINAL

FFA CUP

COMMONWEALTH GAMES

TOUR DE FRANCE

AUDIENCE OVERLAP: SPORTS

Conclusions
• Some observations:
– Distinct diverging footprints for shows
despite shared themes
– Persistent partisan audiences for some
types of programming
– Potential to assess shows based on:
• Ability to reach core audiences
• Ability to engage casual viewers
– Opportunities to:
• Identify lead users / influencers
• Study engagement patterns per episode
• Study engagement patterns over time
– Next steps:
• Develop methods and metrics to
quantify engagement patterns
• Include temporal dimension to track
engagement spread over time
deep
AFLGF
narrow broad
shallow
60Mins
Q&A
Project
BBAU
NRLGF
FFACup
CGames
TdF
(non-scientific illustration)

http://mappingonlinepublics.net/
@snurb_dot_info
@dpwoodford
@katieprowd
@tsadkowsky
@timhighfield
@jeanburgess
@socialmediaQUT – http://socialmedia.qut.edu.au/
This research is funded by the Australian Research Council through Future Fellowship and LIEF
grants FT130100703 and LE140100148.