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

Easy Data, Hard Data? Twitter Research and the Politics of Data AccessAxel Bruns and Jean BurgessARC Centre of Excellence for Creative Industries and InnovationQueensland University of TechnologyBrisbane, Australia

a.bruns / je.burgess @ qut.edu.au

@snurb_dot_info / @jeanburgess

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

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

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)

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

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

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)

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

• interpersonalcommunication,

ephemeral

micro:@replies

(Bruns & Moe, 2013)

‘HARD’ TWITTER RESEARCH APPROACHES

• Context on Twitter:– Meso:

• Underlying follower/followee network structures• Dissemination of information across the follower network• Dynamics of follower relationships

MESO: FOLLOWER NETWORKS

PerthMarketing / PR

DesignWeb

Creative

FarmingAgriculture

HardlineConservatives

ConservativesJournalists

ALPProgressives

Greens

News

OpinionNews

NGOsSocial Policy

ITTech

Social MediaTechPR

Advertising

Real EstateProperty

JobsHR

Business

BusinessProperty

Parenting

Mums CraftArts

FoodWine

Beer

Adelaide

SocialICTs

CreativeDesign

FashionBeauty

UtilitiesServices

Net Culture

BooksLiteraturePublishing

Film

TheatreArts

RadioTV Music

DanceHip Hop

Triple J

TalkbackBreakfast TVCelebritiesCycling

Union

NRL

Football

CricketAFL

SwimmingV8s

Evangelicals

Teachinge-Learning

Schools

ChristiansHillsong

Teens

Jonas Bros.Beliebers

Australian Bands

@KRuddMP

@JuliaGillard

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

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)

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)

MESO: FOLLOWER DYNAMICS

‘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

DYNAMIC: PATTERNS OF URL SHARING

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/)

‘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

http://mappingonlinepublics.net/

@snurb_dot_info

@jeanburgess

@lena_sauter

@dpwoodford

@timhighfield

@socialmediaQUT – http://socialmedia.qut.edu.au/