The document discusses a comprehensive study on Australian Twitter use conducted by Queensland University of Technology, emphasizing Twitter's significance as a social network for research. It outlines methodologies for data gathering and processing, examines the role of hashtags as a means of creating publics, and proposes research questions about the formation and dynamics of online communities. The project aims to better understand Twitter as part of the larger media ecology, while addressing the challenges of analyzing 'big data' in social media research.

1. Twitter, Big Data, and
the Search for Meaning:
Methodology in Progress
Associate Professor Axel Bruns
@snurb_dot_info
http://mappingonlinepublics.net/
Queensland University of Technology

2. WHY TWITTER?
• Researching Twitter:
– Significant world-wide social network
– ~500 million accounts (but how many active?)
– Varied range of uses: from phatic communication to emergency coordination
– Healthy third-party ecosystem (for now)
– Strong history of user innovation:
@replies, #hashtags
– Flat and open network structure:
non-reciprocal following, public profiles by default
– Good API for gathering (big) data for research

3. NEW MEDIA AND PUBLIC COMMUNICATION:
MAPPING AUSTRALIAN USER -CREATED CONTENT
IN ONLINE SOCIAL NETWORKS
• Australian Research Council (ARC) Discovery Project (2010-13) – $410,000
– QUT (Brisbane), Sociomantic Labs (Berlin)
– First comprehensive study of Australian social media use
– Computer-assisted cultural analysis: tracking, mapping, analysing blogs, Twitter, Flickr,
YouTube as ‘networked publics’
– Addressing the problem of scale (‘Big Data’) and disciplinary change in media, cultural and
communication studies – natively digital methods
– Studying society with the Internet (Richard Rogers)
 http://mappingonlinepublics.net/

4. A TWITTER RESEARCH TOOLKIT
• Data Gathering
– yourTwapperkeeper + in-house crawler
• Data Processing
– Gawk – open source, multiplatform, programmable command-line tool for
processing CSV documents
• Textual Analysis
– Leximancer – commercial, multiplatform: extracts key concepts from large
corpora of text, examines and visualises concept co-occurrence
– WordStat – commercial, PC-only text analysis tool; generates concept co-
occurrence data that can be exported for visualisation
• Visualisation
– Gephi – open source, multiplatform network visualisation tool

5. SO NOW WHAT?

6. #HASHTAGS AS PUBLICS
• #hashtags
– ‘#’ + keyword makes tweets easily discoverable and marks themes
– E.g. #ausvotes, #qldfloods, #londonriots, #royalwedding, #euro2012, …
• Publics
– Attend to matters of shared concern with some level of co-awareness
– Varied in intensity and temporality
– Emergent, constituted via discourse & affect
• #hashtag publics
– Not all hashtags constitute publics; Twitter doesn’t ‘contain’ publics
– What are the patterns in the dynamics of different hashtag-based publics?
– What might account for these differences?

7. #SPILL: 23 JUNE 2010, 6-7 P.M.
http://mappingonlinepublics.net/2010/12/30/visualising-twitter-dynamics-in-gephi-part-2/

8. #SPILL: 23 JUNE 2010, 7-8 P.M.

9. #SPILL: 23 JUNE 2010, 8-9 P.M.

10. BUT WHY?
• Possible research questions:
– Ad hoc events and publics:
• How do online publics form and dissolve? How do they interact, what
structures do they form?
• Where do they draw information from? What do they share?
• Do they simply consist of the usual suspects? How insular and disconnected
are online publics?
– Hashtags in context:
• How do different hashtag events compare? Are there common types of
hashtags/publics?
• How ‘big’ are they? What topics attract attention on Twitter?
• What community (?) structures emerge?

11. DEVELOPING TWITTER METRICS
• Key data points available through the Twitter API:
– text: contents of the tweet itself, in 140 characters or less
– to_user_id: numerical ID of the tweet recipient (for @replies)
– from_user: screen name of the tweet sender
– id: numerical ID of the tweet itself
– from_user_id: numerical ID of the tweet sender
– iso_language_code: code (e.g. en, de, fr, ...) of the sender’s default language
– source: client software used to tweet (e.g. Web, Tweetdeck, ...)
– profile_image_url: URL of the tweet sender’s profile picture
– geo_type: format of the sender’s geographical coordinates
– geo_coordinates_0: first element of the geographical coordinates
– geo_coordinates_1: second element of the geographical coordinates
– created_at: tweet timestamp in human-readable format
– time: tweet timestamp as a numerical Unix timestamp

12. DEVELOPING TWITTER METRICS
• Additional data points from tweets:
– original tweets: tweets which are neither @reply nor retweet
– retweets: tweets which contain RT @user… (or similar)
• unedited retweets: retweets which start with RT @user…
• edited retweets: retweets do not start with RT @user…
– genuine @replies: tweets which contain @user, but are not retweets
– URL sharing: tweets which contain URLs
• Potential uses:
– metrics per hashtag
– metrics per timeframe (day, hour, minute, second, …)
– metrics per user (or group of users)
– …
(Bruns & Stieglitz, forthcoming)

13. #QLDFLOODS @REPLIES
authorities
mainstream
media

14. #ROYALWEDDING

15. #AUSPOL (FEB.-DEC. 2011)

16. HASHTAG METRICS

17. TOWARDS A TYPOLOGY
OF TWITTER USES
• How are hashtags used (during acute events)?
– Gatewatching:
• Finding and sharing information about breaking news (before the
mainstream media do?)
• Ad hoc publics: many URLs, many retweets (even unedited)
– Audiencing:
• Shared experience of major (foreseen) events
• Imagined community of fellow participants: few URLs, limited retweeting
• What other uses are there?
– Continuing discussions (#auspol, #bundesliga, …)
– Memes (#ghettohurricanenames, …)
– Emotive hashtags (#fail, #win, #headdesk, …)
– What about keywords?

18. BEYOND HASHTAGS
• Publics on Twitter:
– Micro: @reply and retweet conversations
– Meso: follower/followee networks
– Macro: hashtag ‘communities’ (Bruns & Moe, forthcoming)
 Multiple overlapping publics / networks
• What drives their formation and dissipation?
• How do they interact and interweave?
• How are they interleaved with the wider media ecology?
• Twitter doesn’t contain publics: publics transcend Twitter

19. UNDERSTANDING AUSTRALIAN TWITTER USE
• What is the Australian Twitter userbase?
– Large-scale snowballing project
– Starting from selected hashtag communities
(e.g. #ausvotes, #qldfloods, #masterchef)
– Identifying participating users, testing for ‘Australianness’:
• Timezone setting, location information, profile information
– Retrieving follower/followee information for each account (very slow)
• Progress update:
– ~1.06 million Australian users identified so far
 ~2 million Australian users in total?

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

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

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

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

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

25. 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

26. AUSTRALIAN TWITTER NEWS INDEX
• ATNIX:
– Tracking tweets which link to 29 key Australian news / opinion sites
(even if URLs are shortened: e.g. t.co  bit.ly  ow.ly  abc.net.au)
– Regular processing and evaluation
• Potential uses:
– Examination of general market share
– Impact of key events and stories
– Tracking of specific articles
– Examination of retweet chains for new URLs – how does news
disseminate?
– Coming soon: DeTNIX (Germany), others?

27. TWITTER AND/IN THE MEDIA ECOLOGY

28. TWITTER AND/IN THE MEDIA ECOLOGY

29. 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

30. ‘BIG DATA’ AND THE DIGITAL HUMANITIES
• Emerging needs in Twitter research:
– Unified, compatible methods and metrics for Twitter analysis
 Tools and approaches shared at http://mappingonlinepublics.net/
– Powerful infrastructure for long-term, high-volume tracking of public
communication on Twitter
 Data access requires substantial funding stream
– Facilities for long-term data storage and preservation
 Key roles for National Libraries, National Archives
– Integration with related datasets (e.g. MSM content)
 Need to address data interoperability questions
• Twitter as a test case for digital humanities research
– Widespread, open, public platform for everyday communication
– Tool for observing society at scale through Internet research

31. ‘BIG DATA’ AND STUDENT SKILLS
• Students 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, …)

32. http://mappingonlinepublics.net/
@snurb_dot_info
@jeanburgess
@_StephenH
@DrTNitins
@timhighfield
@cdtavijit