Analysing the Norwegian Twittersphere
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Plenary presentation at the Forskningsdagene, Norwegian National Gallery, Oslo, 28 Sep. 2016.
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Analysing the Norwegian Twittersphere
- 1. Analysing the Norwegian Twittersphere Prof. Axel Bruns Digital Media Research Centre Queensland University of Technology Brisbane, Australia a.bruns@qut.edu.au | @snurb_dot_info
- 2. Twitter: State of the Field • 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
- 3. Mapping the Twittersphere • 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) – Third iteration: full crawl of global Twitter ID numberspace through to Dec. 2015 (~1.4b accounts) – National filters: • Filtering by description, location, timezone, language fields as appropriate • Focus on identifiably local cities, states, timezones and other markers • 2.8 million Australian accounts identified by Sep. 2013; 3.7 million by Dec. 2015 • Retrieval of their follower/followee lists • Best guess of account location based on timezone, location and description settings
- 7. 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 2.8m known Australian accounts as of Sep. 2013 Network of follower connections Filtered for degree ≥1000 140k nodes (~5%), 22.8m edges Labels assigned through qualitative evaluation
- 8. Mapping the Norwegian Twittersphere • Selection criteria: – Interface language = ‘no’ or ‘nb’, or – User location mentions one of ~100 largest towns, ~90 municipalities, ~20 counties, or Norway/…, or – User description mentions one of the locations, or other clearly Norwegian terms – False positives removed (e.g. Bergen, NJ; Oslo, MN; “in den Bergen”; …) – No matching on timezone: no specifically Norwegian timezone offered by Twitter • Results: – 967,560 Norwegian Twitter accounts as of Dec. 2015 – 38,807 protected accounts (~4%) – 219 verified accounts • Follower/followee network amongst Norwegian accounts: – 716,076 accounts follow at least one other Norwegian account – 32,534,829 follower/followee relationships between them
- 11. The Norwegian Twittersphere 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Network visualisation: Force Atlas 2 in Gephi, edges not shown Node colour + size reflects indegree (spline applied)
- 12. CLUSTERS 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Network visualisation: Force Atlas 2 in Gephi, edges not shown Node colours: Gephi, modularity resolution 0.5 The Norwegian Twittersphere
- 13. CLUSTERS 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Node colours: Gephi, modularity resolution 0.5 Cluster assignments by qualitative evaluation The Norwegian Twittersphere Blogs & Humour Football Netizens Politics Music & Radio National News & Culture Online Entertainment Comedy Travel & Leisure Politics: Environment Cultural Debate Science & Innovation Social Politics Religion & Politics Business & Media Trønderlag Sunnmøre Photography Hordaland & Bergen Gambling Sexuality
- 14. VERIFIED / PROTECTED / LANG 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Network visualisation: Force Atlas 2 in Gephi, edges not shown Node colours: red = verified / blue = not verified The Norwegian Twittersphere
- 15. 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Network visualisation: Force Atlas 2 in Gephi, edges not shown Node colours: red = protected / blue = public The Norwegian Twittersphere
- 16. 716,076 accounts with degree ≥1 32,534,829 follower/followee relationships between them Network visualisation: Force Atlas 2 in Gephi, edges not shown Node colours: red = english / blue = Norwegian user interface The Norwegian Twittersphere nb
- 18. Cluster Growth over Time
- 19. 2006-2015 Network maps The Norwegian Twittersphere Accounts created in 2006
- 20. The Norwegian Twittersphere Accounts created in 2007
- 21. The Norwegian Twittersphere Accounts created in 2008
- 22. The Norwegian Twittersphere Accounts created in 2009
- 23. The Norwegian Twittersphere Accounts created in 2010
- 24. The Norwegian Twittersphere Accounts created in 2011
- 25. The Norwegian Twittersphere Accounts created in 2012
- 26. The Norwegian Twittersphere Accounts created in 2013
- 27. The Norwegian Twittersphere Accounts created in 2014
- 28. The Norwegian Twittersphere Accounts created in 2015
- 29. Towns / Counties
- 30. 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 FRISAM project “The Impact of Social Media on Agenda-Setting in Election Campaigns”, and by the Australian Research Council through Future Fellowship and LIEF grants FT130100703 and LE140100148.