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Social Media in Australia: The Case of Twitter

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Invited lecture at the Defence Science and Technology Group, Adelaide, 24 Sep. 2015.

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Social Media in Australia: The Case of Twitter

  1. 1. Social Media in Australia: The Case of Twitter Professor Axel Bruns Digital Media Research Centre Queensland University of Technology Brisbane, Australia a.bruns @ qut.edu.au @snurb_dot_info http://mappingonlinepublics.net/
  2. 2. QUT DIGITAL MEDIA RESEARCH CENTRE The Digital Media Research Centre (DMRC) conducts world-leading research that helps society understand and adapt to the social, cultural and economic transformations associated with digital media technologies, and trains the researchers of tomorrow. For more, see: http://www.qut.edu.au/research/dmrc
  3. 3. Journalism, Public Communication & Democracy Economies, Policies & Regulation Digital Methods Technologies & Practices in Everyday Life DIGITAL MEDIA DMRC PROGRAMMES
  4. 4. RESEARCH PROJECT • ARC Future Fellowship: – Four-year project – Axel Bruns (FF), Brenda Moon (Postdoc), Felix Münch (PhD1, 2014-2017); PhD2 (2016-2018) – enquire within At the intersection of mainstream, niche, and social media, the processes by which public opinion forms and public debate unfolds are increasingly complex, and poorly understood. This project draws on large datasets and innovative methods to develop a new model of the Australian online public sphere. • Also supported by ARC LIEF project: – Two-year project (2014/15; QUT, Curtin, Deakin, Swinburne) to develop comprehensive infrastructure for large-scale social media data analytics
  5. 5. 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 • Best guess of account location based on timezone, location and description settings
  6. 6. WHY ARE WE DOING THIS? • Twitter research to date: – Abundance of hashtag studies: volumetrics, keywords, networks, … – Some studies profiling samples of the total userbase (e.g. celebrities, politicians) – Some comprehensive (?) tracking of activities around key events and topics – Some egocentric follower network maps, largely small-scale – Almost absent: comprehensive follower network maps, longitudinal userbase development trajectories, user career patterns from sign-up to listener/celebrity/… • The political economy of Twitter research: – Twitter API data access is shaped to privilege certain approaches – Research funding is easier to obtain for specific, limited purposes – Longitudinal, ‘big’ data access requires ongoing, substantial funding and infrastructure – Exploratory, data-driven research is difficult to sell to most funding bodies – Also related to divergent resources available to different scholarly disciplines  Most ‘hard data’ Twitter research conducted by Twitter, Inc. and commercial research institutes
  7. 7. BEYOND HASHTAGS • Key needs in Twitter research: – Understand how hashtags are situated in a wider communicative ecology on Twitter – Document the day-to-day uses of Twitter, beyond and outside hashtags – Trace the dynamics of Twitter as a platform for everyday quasi-private, interpersonal, and/or public communication – Track the impact of social and technological changes on these uses • ad hoc publics, often rapidly forming and dissolving macro: #hashtags • personal publics, accumulating slowly and relatively stable meso: follower networks • interpersonal communication, ephemeral micro: @replies (Bruns & Moe, 2013)
  8. 8. DAILY GROWTH (GLOBAL)
  9. 9. MONTHLY GROWTH (AUSTRALIA)
  10. 10. MAPPING THE AUSTRALIAN USERBASE • 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 – Exploration of key profile statistics (join date, number of tweets, tweeting rate) • Activity Patterns: – Data gathered on selected tweeting activities (hashtag participation, link sharing, …) – Data filtered for participating accounts included in the 140k most connected users – Data superimposed on underlying network map • Applications: – Combined analysis of network structures and tweeting activities – Evaluation of user engagement across topics – Comparative benchmarking across activities
  11. 11. Education Agriculture Literature Adelaide / SA Food Wine Beer Parenting Mums PR Netizens Marketing Investing Real Estate Home Business Sole Traders Self-Help HR / Support Followback Urban Media Utilities Advertising Business Fashion Beauty Arts Cinema Journalists Politics Hard RightLeftists News CyclingTalkback Music TV V8s UFC NRL AFL Football Horse Racing Cricket NRU Celebrities Hillsong Perth Pop Media Teen Idols Cody Simpson THE AUSTRALIAN TWITTERSPHERE
  12. 12. PROTECTED (~3.5%)
  13. 13. VERIFIED (~1.8%)
  14. 14. NUMBER OF TWEETS
  15. 15. ACCOUNTS CREATED IN 2006
  16. 16. ACCOUNTS CREATED IN 2007
  17. 17. ACCOUNTS CREATED IN 2008
  18. 18. ACCOUNTS CREATED IN 2009
  19. 19. ACCOUNTS CREATED IN 2010
  20. 20. ACCOUNTS CREATED IN 2011
  21. 21. ACCOUNTS CREATED IN 2012
  22. 22. ACCOUNTS CREATED IN 2013
  23. 23. LOCATION
  24. 24. USER ENGAGEMENT PATTERNS • Datasets included: – Q&A: political talkshow, Australian Broadcasting Corporation – #qanda, qanda (3 Sep. to 7 Oct. 2014) – Big Brother: reality TV, Nine Network – #BBAU, #BBAU9, @BBAU9, #bigbrotherau (3 Sep. to 7 Oct. 2014) – AFL Grand Final: Seven Network – #AFLGF, AFL, HAWvSYD … (27 Sep. 2014, tracked since 26 Sep.) – ABC News: main public broadcaster – abc.net.au (June 2012 to Sep. 2014) – news.com.au: mainstream news site – news.com.au (June 2012 to Sep. 2014) – Daily Telegraph: tabloid newspaper – dailytelegraph.com.au (June 2012 to Sep. 2014) – The Conversation: scholarly opinion site – theconversation.edu.au/.com (June 2012 to Sep. 2014)
  25. 25. AFL GRAND FINAL
  26. 26. Q&A
  27. 27. BIG BROTHER
  28. 28. AUSTRALIAN TWITTER NEWS INDEX (ATNIX) • Data gathering: – All tweets containing links to one of ~35 Australian news sites – Includes tweets with shortened links (t.co, bit.ly, etc.) – Continuous data gathering since August 2012 (with some outages) • Analysis: – Overall development of sharing patterns – Marketshare of specific news organisations – In-depth analysis of day-to-day trends in sharing activity – Correlation with local, regional, and global events • Similar projects in place for Germany and the Nordic countries
  29. 29. ABC NEWS
  30. 30. NEWS.COM.AU
  31. 31. DAILY TELEGRAPH
  32. 32. THE CONVERSATION
  33. 33. TRACKING AUSTRALIAN TWITTER ACTIVITY • Next steps: – Tracking 2.8m Australian Twitter users’ public tweets continuously – Comprehensive dataset of Australian Twitter activities – Full coverage beyond predetermined hashtags / keywords – Important resource for rapid response analytics – Valuable dataset for longer-term historical research – Live tracker now operational, using Sep. 2013 userbase – Need to regather full Australian userbase in 2015
  34. 34. AUSTRALIAN TWEETS PER DAY
  35. 35. LEADING HASHTAGS IN AUSTRALIA
  36. 36. MOST @MENTIONED USERS IN AUSTRALIA
  37. 37. http://mappingonlinepublics.net/ @snurb_dot_info @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.

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