Easy Data, Hard Data?
Twitter Research and the
Politics of Data Access
Axel Bruns and Jean Burgess
ARC Centre of Excellenc...
SOCIAL MEDIA RESEARCH AND ‘BIG DATA’
• Social media as the ‘big data’ moment in
HASS research
• But ‘big data’ + ‘social m...
Scott A.
Golder*, Michael W.
Macy (2011) Diurnal
and Seasonal Mood
Vary with
Work, Sleep, and Day
length Across Diverse
Cu...
SOCIAL MEDIA RESEARCH AND ‘BIG DATA’
• ‘Computational turn’ in new humanities
research: shift from computational tools to ...
CHALLENGES
• Better integration between existing social and cultural
theory & empirical work
• Data access, platform volat...
EASY DATA, HARD DATA
•

Twitter research to date:
– Abundance of hashtag studies: volumetrics, keywords, networks, …
– Som...
HARD DATA

Leetaru et al., 2013:
“Network map showing locations of users retweeting other users (geocoded Twitter Decahose...
BEYOND HASHTAGS
macro:
#hashtags

meso:
follower networks

micro:
@replies

• ad hoc publics,
often rapidly forming
and di...
‘HARD’ TWITTER RESEARCH APPROACHES
•

Context on Twitter:
– Meso:
• Underlying follower/followee network structures
• Diss...
Real Estate
Property

Jobs
HR
Business

Parenting

MESO: FOLLOWER NETWORKS
Design
Web
Creative

Perth
Marketing / PR

Farm...
MESO: INFORMATION DISSEMINATION

Dissemination of Julia Gillard’s “misogyny” speech, 9 Oct. 2012
(from Bruns & Sauter, “An...
MESO: INFORMATION DISSEMINATION

Dissemination of Julia Gillard’s “misogyny” speech, 9 Oct. 2012
(from Bruns & Sauter, “An...
MESO: FOLLOWER DYNAMICS
‘HARD’ TWITTER RESEARCH APPROACHES
•

Context on Twitter:
–

–

–

Meso:
• Underlying follower/followee network structures...
DYNAMIC: PATTERNS OF URL SHARING
DYNAMIC: HOW TWITTER BEGAN
Twitter IDs 1-1,000,000 (48,000 accounts still in existence)
(see http://mappingonlinepublics.n...
‘HARD’ TWITTER RESEARCH APPROACHES
•

Context on Twitter:
– Meso:
• Underlying follower/followee network structures
• Diss...
http://mappingonlinepublics.net/
@snurb_dot_info
@jeanburgess
@lena_sauter
@dpwoodford
@timhighfield

@socialmediaQUT –
ht...
Easy Data, Hard Data? Twitter Research and the Politics of Data Access
Easy Data, Hard Data? Twitter Research and the Politics of Data Access
Easy Data, Hard Data? Twitter Research and the Politics of Data Access
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Easy Data, Hard Data? Twitter Research and the Politics of Data Access

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Paper presented by Axel Bruns and Jean Burgess at the symposium "Compromised Data", Toronto, 28 Oct. 2013.

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Easy Data, Hard Data? Twitter Research and the Politics of Data Access

  1. 1. Easy Data, Hard Data? Twitter Research and the Politics of Data Access Axel Bruns and Jean Burgess ARC Centre of Excellence for Creative Industries and Innovation Queensland University of Technology Brisbane, Australia a.bruns / je.burgess @ qut.edu.au @snurb_dot_info / @jeanburgess
  2. 2. SOCIAL MEDIA RESEARCH AND ‘BIG DATA’ • Social media as the ‘big data’ moment in HASS research • But ‘big data’ + ‘social media’ almost always = ‘Twitter data’ • Computational social science – e.g. MSR NYC; epidemiology; election & stock market prediction
  3. 3. Scott A. Golder*, Michael W. Macy (2011) Diurnal and Seasonal Mood Vary with Work, Sleep, and Day length Across Diverse Cultures, Science 333 (6051): 1878-1881
  4. 4. SOCIAL MEDIA RESEARCH AND ‘BIG DATA’ • ‘Computational turn’ in new humanities research: shift from computational tools to a new computational paradigm (Berry, 2012). • Eg shift from ‘close’ to ‘distant’ reading (Moretti); ‘software studies’ (eg Fuller, 2008) and ANT approaches to new media platforms; ‘natively’ digital methods to diagnose patterns of social change (Rogers, 2009). • Intersections between data-driven social media research & critical platform studies (Gillespie)
  5. 5. CHALLENGES • Better integration between existing social and cultural theory & empirical work • Data access, platform volatility – Easy data, hard data – Dynamics politics of platform change an object of study in themselves
  6. 6. EASY DATA, HARD DATA • 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. HARD DATA Leetaru et al., 2013: “Network map showing locations of users retweeting other users (geocoded Twitter Decahose tweets 23 October 2012 to 30 November 2012)” (http://firstmonday.org/ojs/index.php/fm/article/view/4366/3654)
  8. 8. BEYOND HASHTAGS macro: #hashtags meso: follower networks micro: @replies • ad hoc publics, often rapidly forming and dissolving • personal publics, accumulating slowly and relatively stable • interpersonal communication, ephemeral (Bruns & Moe, 2013) • 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
  9. 9. ‘HARD’ TWITTER RESEARCH APPROACHES • Context on Twitter: – Meso: • Underlying follower/followee network structures • Dissemination of information across the follower network • Dynamics of follower relationships
  10. 10. Real Estate Property Jobs HR Business Parenting MESO: FOLLOWER NETWORKS Design Web Creative Perth Marketing / PR Farming Agriculture IT Tech News Food Wine Creative Design Social ICTs Fashion Beauty Utilities Services Net Culture Opinion News ALP Progressives Craft Arts Beer NGOs Social Policy Greens Hardline Conservatives Social Media Tech PR Advertising Mums Business Property Books Literature Publishing Adelaide Theatre Film Arts @KRuddMP @JuliaGillard Conservatives Journalists Radio TV Music Triple J Talkback Breakfast TV Cycling Celebrities Dance Hip Hop Union Evangelicals NRL Swimming V8s Football Follower/followee network: ~120,000 Australian Twitter users (of ~950,000 known accounts by early 2012) colour = outdegree, size = indegree Cricket AFL Christians Teaching Hillsong e-Learning Schools Teens Jonas Bros. Beliebers
  11. 11. MESO: INFORMATION DISSEMINATION Dissemination of Julia Gillard’s “misogyny” speech, 9 Oct. 2012 (from Bruns & Sauter, “Anatomie eines Trending Topics”, DGPuk Vienna, 8 Nov. 2013)
  12. 12. MESO: INFORMATION DISSEMINATION Dissemination of Julia Gillard’s “misogyny” speech, 9 Oct. 2012 (from Bruns & Sauter, “Anatomie eines Trending Topics”, DGPuk Vienna, 8 Nov. 2013)
  13. 13. MESO: FOLLOWER DYNAMICS
  14. 14. ‘HARD’ TWITTER RESEARCH APPROACHES • Context on Twitter: – – – Meso: • Underlying follower/followee network structures • Dissemination of information across the follower network • Dynamics of follower relationships Micro: • @mentions between identified user populations • Conversational patterns (e.g. @reply / retweet chains) • Participant career types (listener, engager, influencer, celebrity, …) Dynamic: • Global / national / local volumes of overall Twitter activity • Thematic fluctuations in day-to-day activity • Patterns in URL dissemination
  15. 15. DYNAMIC: PATTERNS OF URL SHARING
  16. 16. DYNAMIC: HOW TWITTER BEGAN 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/)
  17. 17. ‘HARD’ TWITTER RESEARCH APPROACHES • Context on Twitter: – Meso: • Underlying follower/followee network structures • Dissemination of information across the follower network • Dynamics of follower relationships – Micro: • @mentions between identified user populations • Conversational patterns (e.g. @reply / retweet chains) • Participant career types (listener, engager, influencer, celebrity, …) – Dynamic: • Global / national / local volumes of Twitter activity • Thematic fluctuations in day-to-day activity • Patterns in URL dissemination • Twitter in context: – – – – Broader patterns of social media adoption and use Media coverage of Twitter as an indicator of societal perceptions Interlinkages with other media channels: Twitter in transmedia events Effects of Twitter, Inc.’s commercial positioning and technological development
  18. 18. http://mappingonlinepublics.net/ @snurb_dot_info @jeanburgess @lena_sauter @dpwoodford @timhighfield @socialmediaQUT – http://socialmedia.qut.edu.au/
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