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Mapping Social TV Audiences: The Footprints of Leading Shows in the Australian Twittersphere

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Paper by Axel Bruns, Darryl Woodford, Tim Highfield, and Katie Prowd, presented at the Association of Internet Researchers conference, Daegu, Korea, 22-25 Oct. 2014.

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Mapping Social TV Audiences: The Footprints of Leading Shows in the Australian Twittersphere

  1. 1. 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/
  2. 2. 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
  3. 3. 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
  4. 4. 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)
  5. 5. 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
  6. 6. 60 MINUTES
  7. 7. Q&A
  8. 8. THE PROJECT
  9. 9. BIG BROTHER
  10. 10. AUDIENCE OVERLAP: POLITICS
  11. 11. AFL GRAND FINAL
  12. 12. NRL GRAND FINAL
  13. 13. FFA CUP
  14. 14. COMMONWEALTH GAMES
  15. 15. TOUR DE FRANCE
  16. 16. AUDIENCE OVERLAP: SPORTS
  17. 17. 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)
  18. 18. 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.

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