Twittersphere – QUT Social Media Research Group https://socialmedia.qut.edu.au Tue, 10 Apr 2018 02:59:25 +0000 en-US hourly 1 https://wordpress.org/?v=6.7.2 Live Trends in the Australian Twittersphere https://socialmedia.qut.edu.au/2018/04/10/live-trends-in-the-australian-twittersphere/ https://socialmedia.qut.edu.au/2018/04/10/live-trends-in-the-australian-twittersphere/#respond Tue, 10 Apr 2018 02:59:25 +0000 http://socialmedia.qut.edu.au/?p=1102 As a first piece of work that builds on QUT’s new Digital Observatory – a collaboration between the QUT Institute for Future Environments and the QUT Digital Media Research Centre – I’m pleased to share a new live dashboard showing overall trends in the Australian Twittersphere.

This builds on our prior work to identify Australian Twitter accounts and map the network structure of the Australian Twittersphere (covered at The Conversation and published in Social Media + Society), and tracks the public posting activities of some 500,000 Australian Twitter accounts on a continuous, real-time basis. For this general overview, we’re pulling out the major hashtags and the most mentioned accounts (counting both @mentions and retweets) – but of course the underlying dataset captures far more than this.

If you’re interested in further research that builds on this dataset, please get in touch!

(Click ‘full screen’ to enlarge.)

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A New Map of the Australian Twittersphere https://socialmedia.qut.edu.au/2018/01/08/a-new-map-of-the-australian-twittersphere/ https://socialmedia.qut.edu.au/2018/01/08/a-new-map-of-the-australian-twittersphere/#respond Mon, 08 Jan 2018 05:43:00 +0000 http://socialmedia.qut.edu.au/?p=1079 Researchers from the QUT Digital Media Research Centre have released a new, detailed analysis of the structure of the Australian Twittersphere. Covering some 3.72 million Australian Twitter accounts, the 167 million follower/followee connections between them, and the 118 million tweets posted by these accounts during the first quarter of 2017, a new article by Axel Bruns, Brenda Moon, Felix Münch, and Troy Sadkowsky, released in December 2017 in the open-access journal Social Media + Society, maps the structure of the best-connected core of the Australian Twittersphere network:

The Australian Twittersphere in 2016: Mapping the Follower/Followee Network

Twitter is now a key platform for public communication between a diverse range of participants, but the overall shape of the communication network it provides remains largely unknown. This article provides a detailed overview of the network structure of the Australian Twittersphere and identifies the thematic drivers of the key clusters within the network. We identify some 3.72 million Australian Twitter accounts and map the follower/followee connections between the 255,000 most connected accounts; we utilize community detection algorithms to identify the major clusters within this network and examine their account populations to identify their constitutive themes; we examine account creation dates and reconstruct a timeline for the Twitter adoption process among different communities; and we examine lifetime and recent tweeting patterns to determine the historically and currently most active clusters in the network. In combination, this offers the first rigorous and comprehensive study of the network structure of an entire national Twittersphere.

A summary of some of the study’s key findings was published in The Conversation in May 2017. Meanwhile, a paper by Axel Bruns at the Future of Journalism conference in Cardiff in September 2017 built on this new Twittersphere map to test for the existence of echo chambers and filter bubbles in Australian Twitter – and found little evidence to support the thesis:

Echo Chamber? What Echo Chamber? Reviewing the Evidence

The success of political movements that appear to be immune to any factual evidence that contradicts their claims – from the Brexiteers to the ‘alt-right’, neo-fascist groups supporting Donald Trump – has reinvigorated claims that social media spaces constitute so-called ‘filter bubbles’ or ‘echo chambers’. But while such claims may appear intuitively true to politicians and journalists – who have themselves been accused of living in filter bubbles –, the evidence that ordinary users experience their everyday social media environments as echo chambers is far more limited.

For instance, a 2016 Pew Center study has shown that only 23% of U.S. users on Facebook and 17% on Twitter now say with confidence that most of their contacts’ views are similar to their own. 20% have changed their minds about a political or social issue because of interactions on social media. Similarly, large-scale studies of follower and interaction networks on Twitter show that national Twitterspheres are often thoroughly interconnected and facilitate the flow of information across boundaries of personal ideology and interest, except for a few especially hardcore partisan communities.

Building on new, comprehensive data from a project that maps and tracks interactions between 4 million accounts in the Australian Twittersphere, this paper explores in detail the evidence for the existence of echo chambers in that country. It thereby moves the present debate beyond a merely anecdotal footing, and offers a more reliable assessment of the ‘echo chamber’ threat.

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Twitter in Australia: How We’ve Grown and What We Talk About https://socialmedia.qut.edu.au/2017/05/03/twitter-in-australia-how-weve-grown-and-what-we-talk-about/ https://socialmedia.qut.edu.au/2017/05/03/twitter-in-australia-how-weve-grown-and-what-we-talk-about/#respond Wed, 03 May 2017 07:15:11 +0000 http://socialmedia.qut.edu.au/?p=1059 There are plenty of assumptions and not a great deal of reliable data about how we use social media. Twitter, for example, is variously accused of being a haven for leftist outrage and a cesspool of alt-right fascists; it is seen as a crucial tool for crisis communication and a place where millennials share photos of their lunch. Surely, these can’t all be true at the same time.

Part of the problem here is that we all design our own filter bubbles, as the journalism researcher Paul Bradshaw has put it: what two random users see of Twitter might be entirely different, depending on what other accounts they choose to follow. If all you ever see is food porn, perhaps you’d care to make some new connections. Or perhaps that’s what you’re there for.

But if we could look beyond our own, personal networks, what would we see? What are the major drivers of Twitter take-up, in Australia and elsewhere? Do we connect around shared interests, shared location, or pre-existing offline relationships? And when, in the eleven-year history of the platform, did these structures form?

These are the questions that guided a new, long-term study of the Australian national Twittersphere that my colleagues and I have undertaken. Drawing on TrISMA, a major multi-institutional facility for social media analytics, we identified some 3.7 million Australian Twitter accounts in existence by early 2016, and captured the 167 million follower/followee connections they have amongst each other.

New Accounts per Day

Twitter took off in Australia in 2009, some three years after its launch, and saw a fairly steady sign-up rate of 1,000-2,000 new accounts between 2010 and 2014. Growth has slowed since then, and this may indicate market saturation. There are a number of obvious spikes in new account sign-ups, too: the series of natural disasters in early 2011 attracts users to the platform who recognise its role in crisis communication, and the political turmoil of 2013 also seems to drive take-up.

A major spike in 2015 appears to coincide with the devastating Nepal earthquake, but we’ve yet to determine why that event would lead to new Twitter accounts being created in Australia.

To focus in on the core parts of the network, we further filtered this to accounts that have at least 1,000 connections in the global Twittersphere, which left us with the 255,000 best-connected accounts. We visualised their network using Gephi’s Force Atlas 2 algorithm, which places accounts close to each other if they share many connections, and further apart if they are only poorly connected.

Australian Twittersphere

The network map shows clear clustering tendencies: dense regions, where many accounts are closely connected, are separated from each other by lower-density spaces. We systematically examined these clusters, and labelled them based on the overarching themes that emerged from an analysis of the account profiles in each cluster. The result is a kind of birds-eye view of the Twitter landscape, from politics to popular culture and from education to sports.

Perhaps surprisingly, accounts connecting around teen culture make up the largest part of this network: 61,000 of our 255,000 accounts are located here. Other major clusters include aspirational accounts (these include self-declared social media gurus, self-improvement and life-coaching practitioners, and others who sought to use Twitter for professional betterment), at 26,000 accounts; sports, with 25,000 accounts (including distinct sub-clusters for cycling and horse racing); and netizens, technologists, and software developers (17,000 accounts).

Shared interests emerge from this as the central drivers of our connections on Twitter: for the most part, we follow others because of the topics they cover, not because they’re from the same city or state or because we already know them offline. An equivalent map for Facebook, where connections are much more strongly based on prior acquaintance, would likely look very different.

We further found that these accounts also arrived on Twitter at very different times: both netizen and aspirational accounts were created very early in the history of the platform. As expected, netizens constituted the vast majority of Australia’s early adopters, with aspirational accounts close behind; fully half of the population in both these clusters had arrived on Twitter by mid-2010. Sports took a year longer, and may well have been helped along by Twitter Australia itself as it reached out to key sporting codes to get their teams and players signed up.

11 New accounts in clusters per month

By contrast, the teen culture accounts arrived a great deal later. It took until mid-2012 until half that cluster’s population had joined – the teen invasion of Twitter represents a secondary adoption event, following the first big influx of Australian users in 2009/10. Here, too, we suspect active encouragement from key bands like One Direction and Five Seconds of Summer as a major driver.

In spite of Twitter’s reputation as a space for political debate and agitation, politics attracts only some 13,000 accounts (including 1,500 that form a separate, staunchly right-wing cluster); there’s a great deal more to Twitter than political argument.

But if all you ever see on Twitter is partisan bickering, there may be a reason: per capita, the political accounts are some of the most active in the Australian Twittersphere. Over their lifetimes, they’ve posted an average of 7.2 tweets per day (and the accounts in the hard right cluster even manage 12.5 per day); in the turbulent first quarter of 2017, those averages are even higher. Most of the other major cluster communities have managed less than half that work rate; historically, only the teen culture accounts have been similarly active.

Twitter is what its users make it, and Australian users have made it a diverse and dynamic place, even if perhaps they’re less aware of each other than they should be. As users, we should step beyond our networks more often, to avoid becoming trapped in our own filter bubbles – and this goes doubly for politicians, journalists, and others who now treat their immediate Twitter networks as an instant source of popular opinion.

And as a company, Twitter too has much work to do to enable its users to experience the full variety of networked communication and culture that the platform has to offer. Changes to how it recommends new accounts to follow, and how it reveals trending topics outside of our existing networks, could help a great deal in combatting the threat of getting stuck in your own filter bubble.

It doesn’t stop there, of course. We can only speculate what the equivalent networks for Facebook, Instagram, or Snapchat would look like, and what they might tell us about how people are using these platforms.

(An edited version of this article was published in The Conversation on 3 May 2017.)

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