1. Digital Methods and Social
Media Analytics
Jean Burgess, Axel Bruns, and Darryl Woodford
Media Ecologies Project, CCI
Queensland University of Technology
@jeanburgess | @snurb_dot_info | @dpwoodford
http://mappingonlinepublics.net/

2. DIGITAL METHODS…?
• Datagathering
• Processing
• Analysis
• Re-presentation
• Materiality and ‘nature’ of the digital

3. ‘BIG DATA’ & DIGITAL METHODS
• Big Data as currency across the sciences and social sciences
• Business intelligence & ‘data markets’ (including social media & online
behavioral data).
• Computational social science – e.g. MSR NYC; epidemiology; election &
stock market prediction
• ‘Computational turn’ in new humanities research: shift from computational
tools to a new computational paradigm, changing the ontologies and
epistemologies of humanities research (Berry, 2012).
• Eg shift from ‘close’ to ‘distant’ reading (Moretti); ‘software studies’ (eg
Fuller, 2008) and ANT approaches to new media platforms;
• From ‘virtual’/trad social research methods to ‘natively’ digital methods to
diagnose patterns of social change (Rogers, 2009).

4. The map is not the territory
(Korzybski)
…and certainly not the
destination

5. UNDERSTANDING TWITTER PUBLICS
• #hashtags:
– Useful coordinating mechanism for core discussion
– Relatively easy to capture and analyse
– Fails to capture non-hashtagged tweets about the topic
– Good case studies, but very little comparative work to date
• National / global Twittersphere maps:
– Crucial contextual baseline for #hashtag case studies
– Slow and laborious data gathering process, never complete
– Very long-term perspective, beyond most funded projects
– Indispensable for study of Twitter as a public space

6. #ROYALWEDDING (29 APR. 2011)

7. #AUSVOTES (JULY-AUG. 2010): THEMES

8. #EQNZ: MOST VISIBLE ACCOUNTS, 22 FEB.-7 MAR. 2011
(RETWEETS + @REPLIES RECEIVED)

9. #EQNZ: VISIBILITY ACROSS EARTHQUAKES (2010-2011)
(Bruns & Burgess, 2012)

10. HASHTAGMETRICS
(Bruns &
Stieglitz, 2012)

11. BEYOND HASHTAGS
 Overlapping publics / networks
– What determines their formation and dissolution?
– How do they interact and interweave?
– How are they interleaved with the wider media ecology?
– How do they represent the Twitter component of wider societal publics?
• 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)

12. THE AUSTRALIAN TWITTERSPHERE?
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = outdegree, size = indegree

13. THEMATIC CLUSTERS
Perth
Marketing / PR
Design
Web
Creative
Farming
Agriculture
Hardline
Conservatives
Conservatives
Journalists
ALP
Progressives
Greens
News
Opinion
News
NGOs
Social Policy
IT
Tech
Social Media
Tech
PR
Advertising
Real Estate
Property
Jobs
HR
Business
Business
Property
Parenting
Mums Craft
Arts
Food
Wine
Beer
Adelaide
Social
ICTs
Creative
Design
Fashion
Beauty
Utilities
Services
Net Culture
Books
Literature
Publishing
Film
Theatre
Arts
Radio
TV Music
Dance
Hip Hop
Triple J
Talkback
Breakfast TV
CelebritiesCycling
Union
NRL
Football
Cricket
AFL
Swimming
V8s
Evangelicals
Teaching
e-Learning
Schools
Christians
Hillsong
Teens
Jonas Bros.
Beliebers
@KRuddMP
@JuliaGillard

14. #AUSPOL
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = #auspol tweets, size = indegree

15. #AUSVOTES
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = #ausvotes tweets, size = indegree

16. #ROYALWEDDING
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = #royalwedding tweets, size = indeg.

17. #MASTERCHEF
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = #masterchef tweets, size = indeg.

18. THEAUSTRALIAN.COM.AU URLS
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = tweets with URLs, size = indegree

19. ABC.NET.AU URLS
Follower/followee network:
~120,000 Australian Twitter users
(of ~950,000 known accounts by early 2012)
colour = tweets with URLs, size = indegree

20. AUSTRALIAN TWITTER NEWS INDEX
http://mappingonlinepublics.net/tag/atnix/

21. AUSTRALIAN TWITTER NEWS INDEX

22. BIG BIG DATA: THE FIRST MILLION TWITTER IDS
Twitter IDs 1-1,000,000 (48,000 accounts still in existence)
(see http://mappingonlinepublics.net/2013/04/08/the-first-million-ids-on-twitter/)

23. THE FIRST MILLION: TWEETS SENT

24. THE FIRST MILLION: TIME ZONES

25. A NEW MILLION
• 1 million new account IDs (~ 422.000 existing accounts)
• Newly registered on 18/19 Mar. 2013, 16:00-01:00 UTC ( 1-1.5m new users/day)

26. TWITTER AS A PROXY
• Tweets, and Twitter Users, are actually informative about
other platforms.
• While not an alternative to application specific APIs, it
can provide an approximation.
• Overall pattern / content of uploaded Vine videos (that
are shared via Twitter: ~50%).
• Mirrors YouTubers fairly well (similar start date, ‘Pro’
YouTubers use Twitter/FB to reduce reliance on YT)

27. TWITTER AS A PROXY
• While not an alternative to application specific APIs, it
can provide an approximation of growth rates and user
profiles.
• Overall pattern / content of uploaded Vine videos (that
are shared via Twitter: ~50%).
• Mirrors YouTubers fairly well (similar start date, ‘Pro’
YouTubers use Twitter/FB to reduce reliance on YT)

28. TWITTER AS A PROXY: MONTH OF VINES

29. TWITTER AS A PROXY: DAILY PATTERNS

30. TWITTER AS A PROXY: HASHTAGS AS
DESCRIPTORS

31. TWITTER AS A PROXY: YOUTUBERS:
@CHARLESTRIPPY (ID VS. ACCESSION #)
This set of IDs were
apparently never
allocated.
Prank vs Prank

32. TWITTER AS A PROXY: YOUTUBERS --
@CHARLESTRIPPY (ACC # VS DATE)
PrankvsPrank
?
CTFxC Wedding

33. TWITTER AS A PROXY: YOUTUBERS --
@COREYVIDAL (ACC # VS DATE)
CTFxC Wedding
I’m Vlogging Here Indiegogo
& Filming
?

34. PRACTICAL CHALLENGES
• Data access, platform volatility
• Research ethics
– textual research or ‘human subjects’ research?
– Consequences of public/personal convergence, data
markets/open data movement, and ‘context collapse’ (boyd)
– Cross-national and cross-disciplinary differences, need for public
discussion

35. PRACTICAL CHALLENGES
• Better integration with existing social and cultural theory
& empirical work
– Mixed methods, especially integration of qualitative and
ethnographic approaches
• Propagation and regularisation of methods (and
consequences for research training)
– ‘Code literacy’ sufficient to engage with the material
consequences of software platforms

36. ‘BIG DATA’ AND RESEARCH SKILLS
• Researchers need interdisciplinary skill sets:
– Media & communication to understand the media environment
– Maths and statistics to deal with ‘big data’
– Computer science to develop tools to process social media data
– Communication design to develop effective visualisations
– Writing and communication skills to communicate the results
– …
– Where do we find them?
(few people have such a diverse range of skills)
– How do we support their work?
(we’re only just developing our methods and tools)
– What is our strategy for dealing with precarity?
(sudden API changes, changing fortunes of platforms, …)

37. http://mappingonlinepublics.net/
@snurb_dot_info
@jeanburgess
@dpwoodford
@tsadkowsky
@lena_sauter
@timhighfield
@cdtavijit
@socialmediaQUT