One Day in the Life of a National Twittersphere

One Day in the Life of a National TwittersphereProf. Axel Bruns & Dr. Brenda MoonDigital Media Research CentreQueensland University of TechnologyBrisbane, [email protected] | [email protected]@snurb_dot_info | @brendam

Axel Bruns is currently a visiting scholar at the Alexander-von-Humboldt-Institut for Internet and Society, Berlin.

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

The Australian Twittersphere• Twitter in Australia:

– Strong take-up since 2009– Centred around 25-55 age range, urban, educated, affluent users (but gradually broadening)– Significant role in crisis communication, political communication, audience engagement, …

• 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)

• Filtering by description, location, timezone fields• Focus on identifiably Australian cities, states, timezones and other markers• 2.8 million Australian accounts identified (by Sep. 2013)• Retrieval of their follower/followee lists• Best guess of account location based on timezone, location and description settings

Education

Agriculture

Literature

Adelaide / SA

FoodWine

Beer

Parenting

Mums PR

Netizens

Marketing

InvestingReal Estate

Home BusinessSole Traders

Self-Help

HR / Support

Followback

Urban MediaUtilities

Advertising

Business

Fashion

Beauty

ArtsCinema

Journalists

Politics

Hard RightLeftists

News

CyclingTalkback

Music

TVV8s UFC

NRL

AFL

Football

Horse Racing

CricketNRU

Celebrities

Hillsong

Perth

PopMedia

Teen Idols

Cody Simpson

The Australian Twittersphere2.8m known Australian accountsNetwork of follower connections

Filtered for degree ≥1000140k nodes (~5%), 22.8m edges

Labels assigned through qualitative evaluation

TrISMA: Tracking Australian Twitter• ARC LIEF project:

– Tracking Infrastructure for Social Media Analysis– Multi-university project led by QUT to develop comprehensive infrastructure for large-

scale social media data analytics– Twitter: continuous capture of tweets by all 2.8m identified Australian accounts– 1b+ tweets captured to date, 1m+ new tweets/day– Data storage via Google BigQuery, analysis via Tableau and Gephi

• Basic conventions:– All dates in AEST (UTC+10: Sydney, Melbourne, Brisbane);

other cities up to two hours behind– Tweet types: original, @mention, retweet (RT/MT/HT/via/"@user or retweet button)– Hashtags: A-Z + 0-9 + _, and at least three characters

Twitter in Australia: Overall Patterns2015 Video Music Awards

unique accounts

Twitter in Australia: Overall Patterns

Twitter in Australia: Overall Patterns

ONE (RANDOM) DAY: 6 AUG. 2015(Work in progress!)

Overall Patterns: 6 Aug. 2015

1.1m tweets from 147k, to 224k accounts294k nodes total, including non-Australians535k edges from 856k @mentions / RTs

Visualisation: Gephi, Force Atlas 2Node colours: Gephi, modularity resolution 1.0


Visualisation: Gephi, Force Atlas 2Edge colours: red = @mentions, green = retweets


Visualisation: Gephi, Force Atlas 2Mutual edges only: 37k edges (7.05% of total)

Edge colours: red = @mentions, green = retweets


Visualisation: Gephi, Force Atlas 2Colours: Gephi, modularity resolution 1.0

Labels assigned through qualitative evaluation

Politics

Cricket

Teen CulturePop

Tweeting Activities per Cluster

Hashtags per Cluster

Account Positions in Follower Network

Cluster Interactions

E-I Index ()EII = -1: only internal edges / EII = +1: only external edges

First Observations• Crucial to move Twitter studies beyond hashtag studies:

– Majority of activity outside of hashtags– Follow-on conversations especially important

• Follower and interaction networks intersect:– Significant account interactions across follow network cluster boundaries– Some clusters more than others, some topics more than others (and ‘clusters’ are soft constructs)– Dynamics of such processes still to be understood fully

• Significant differences across Twitter communities:– Inward vs. outward orientation– Retweet vs. @mention interactions– Mutual interaction vs. retweeting of few key accounts

• Different cultures of Twitter use:– Potentially related to age and experience of Twitter users

(e.g. older politics-focussed accounts vs. younger teen accounts)

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 Australian Research Council through Future Fellowship and LIEF grants FT130100703 and LE140100148, and was conducted while visiting the Alexander-von-Humboldt-Institut for Internet and Society.