Invited presentation at the University of Melbourne, 4 April 2017.
Twitter research to date has focussed mainly on the study of isolated events, as described for example by specific hashtags or keywords relating to elections, natural disasters, public events, and other moments of heightened activity in the network. This limited focus is determined in part by the limitations placed on large-scale access to Twitter data by Twitter, Inc. itself. This research presents the first ever comprehensive study of a national Twittersphere as an entity in its own right. It examines the structure of the follower network amongst some 4 million Australian Twitter accounts and the dynamics of their day-to-day activities, and explores the Australian Twittersphere’s engagement with specific recent events.
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Social Media in Australia: A ‘Big Data’ Perspective on Twitter
1. Social Media in Australia:
A ‘Big Data’ Perspective on Twitter
Prof. Axel Bruns
ARC Future Fellow
Digital Media Research Centre
Queensland University of Technology
a.bruns@qut.edu.au – @snurb_dot_info
2. QUT Digital Media Research Centre
The Digital Media Research Centre (DMRC)
conducts world-leading research that helps society
understand and adapt to the social, cultural and
economic transformations associated with digital
media technologies, and trains the researchers of
tomorrow.
For more, see: http://www.qut.edu.au/research/dmrc
4. Research Project
• ARC Future Fellowship:
– Four-year project
– Axel Bruns (FF), Brenda Moon (Postdoc),
Felix Münch (PhD1, 2014-2017), Ehsan Dehghan (PhD2, 2016-2018)
At the intersection of mainstream, niche, and social media, the processes by
which public opinion forms and public debate unfolds are increasingly
complex, and poorly understood. This project draws on large datasets and
innovative methods to develop a new model of the Australian online public
sphere.
• Also supported by ARC LIEF project:
– Two-year project (2014/15; QUT, Curtin, Deakin, Swinburne) to develop
comprehensive infrastructure for large-scale social media data analytics
5. 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)
– Third iteration: full crawl of global Twitter ID numberspace through to Feb. 2016 (~1.4b accounts)
• Filtering by description, location, timezone fields: identifiably Australian cities, states, timezones, etc.
• 4 million Australian accounts identified (by Feb. 2016)
• Retrieval of their follower/followee lists
– Continuous gathering of their public tweets
• Capturing ~1.3m new tweets per day
6. Why are we doing this?
• 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
9. Mapping the Australian Userbase
• Mapping the Twittersphere:
– Filtered to include only accounts with (followers + followees) >= 1000
• ~255k accounts, 61m follower/followee connections within this group
– Mapped using Gephi Force Atlas 2 algorithm (LinLog mode, scaling 0.00001, gravity 1.0)
• Force-directed visualisation: closely interconnected groups of accounts will form clusters in the network
• Clusters in the Twittersphere:
– Identification of clusters using the Louvain community detection algorithm (resolutions 0.5 and 0.25)
– Qualitative interpretation of clusters themes based on high-degree nodes in each cluster
• Applications:
– Combined analysis of network structures and tweeting activities
– Evaluation of potential and actual information flows across the network
– Comparative benchmarking of clusters across different markers
10. The Australian Twittersphere, 2016
4m known Australian accounts
Network of follower connections
Filtered for degree ≥1000
255k nodes (6.4%), 61m edges
Edges not shown in graph
34. 4m known Australian accounts
Network of follower connections
Filtered for degree ≥1000
255k nodes (6.4%), 61m edges
Edges not shown in graph
Clusters
Teen Culture
Aspirational
Sports
Netizens
Arts & Culture
Politics
Television
Fashion
Popular Music
Food & Drinks
Agriculture Activism
Porn
Education
Cycling
News &
Generic
Hard Right
Progressive
South
Australia
Celebrities
Horse Racing
53. Tweets per Cluster (Average)
Colour scale: yellow to red
Non-tweeting accounts in grey
Louvain modularity resolution 0.5
Average over tweeting accounts only
54. Tweets per Cluster (Average)
Colour scale: yellow to red
Non-tweeting accounts in grey
Louvain modularity resolution 0.25
Average over tweeting accounts only