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Social Media Network Mapping

Busy-ness as Usual

This blog has been somewhat slow again since the last round of conferences, and I'm hoping to do more in the future to change this. In the first place, I'm planning to post more regular updates again as I publish new articles and book chapters (watch out for a round-up of recent work soon, most of which already appear in my list of publications). There are also a number of new research projects which have started this year – and while more detailed updates about the day-to-day work of some of these will appear on Mapping Online Publics and the Website of the QUT Social Media Research Group, I'm planning to flag the most important outcomes from these projects here as well. And as always, updates are also available on Twitter through my own account @snurb_dot_info as well as @socialmediaQUT.

New Projects

Most importantly, I've just commenced my ARC Future Fellowship – a major four-year project which builds on my social media work and connects it with a number of other important data sources which shed light on the way Australian Internet users are engaging with news and current affairs. We'll continue to draw on large Twitter data (as well as, eventually, data from other social networks) which show the patterns of day-to-day activity around current events, and we'll correlate these patterns with data from Experian Hitwise, which track (anonymously and at very large scale) how Australian users search and browse the Web. Further, I'm also going to be able to incorporate some internal server data from Fairfax Digital (including its flagship mastheads Sydney Morning Herald and The Age) to investigate in more depth what articles users read and engage with on these sites.

Different Forms of Talk on Twitter

It’s been a little quiet again here, as I’ve taken February and March off on Long Service Leave. That’s all about to change, though, because two major new research projects are about to start now – more of these soon.

For the moment, here’s my first conference presentation for 2014, from the Media Talk symposium at Griffith University in Brisbane. I used this to work through the three layers of communication on Twitter which Hallvard Moe and I have identified in our chapter in Twitter and Society, and to provide some examples for how these layers operate in practice.

This is also the first time I’m trying Penxy as a tool for archiving my slides with audio recordings, since Slideshare has made the unfortunate decision to discontinue its slidecasts and remove any audio recordings from its site. Most of my past slidecasts are therefore also on the Penxy site now, and I’ll try to update the existing links to recorded presentations on this site when I get a chance.

Here’s my talk:

Layers of Communication: Forms of Talk on Twitter

Layers of Communication: Forms of Talk on Twitter (Media Talk 2014)

Media Talk Symposium 2014

Layers of Communication: Forms of Talk on Twitter

Axel Bruns

  • 24 Apr. 2014 – Media Talk Symposium, Brisbane

With some 2.5 million accounts, especially representing the influential 25-55 age range, Twitter has become an important social media platform in Australia. It has found key applications in areas ranging from politics and crisis communication to entertainment and sports, but also facilitates everyday communication between like-minded individuals and communities. In spite of the increased scholarly attention on the uses of Twitter across these practices, however, the question of what kind(s) of communication Twitter represents remains largely underexplored, and the forms of interaction that the platform enables have yet to be fully theorised.

Building on prior work by Bruns & Moe (2014), this paper explores the various layers of communication which exist on Twitter, from direct, dyadic @reply exchanges between clearly identified communication partners at the micro level through narrowcast message dissemination to the followers of an account at the meso level to many-to-many exchanges in ad hoc publics created by hashtags at the macro level. It outlines the different types and formats of talk which are able to occur at each of these levels, and shows the interweaving of the information and communication flows which take place on each of them. In doing so, it outlines the complexities of communication on Twitter, and points to new challenges in Twitter research.

References:

Axel Bruns and Hallvard Moe. (2014). “Structural Layers of Communication on Twitter.” In Twitter and Society, eds. Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt, and Cornelius Puschmann. New York: Peter Lang, 2014. 15-28.

Presenting Our Social Media Work at the 2013 IBM Research Colloquium

Now that I’m back in Australia from my extended conference trip, I immediately got back on a plane to travel to a freezing Melbourne, to present our social media research in crisis communication and beyond at the 2013 IBM Research Colloquium. Below are my slides and audio – many thanks again to Jennifer Lai and her team at IBM Research Australia for the invitation!

Social Media Issue Publics in Australia (IBM Research Colloquium 2013)

IBM Research Colloquium 2013

Social Media Issue Publics in Australia

Axel Bruns

When important news breaks, social media facilitate the rapid formation of issue publics which come together to 'work the story' of the unfolding event. This is especially evident in the context of natural disasters and other crises. The close study of social media feeds during such crisis provides a valuable insight into the dynamics of the event, with participants acting as human sensors for new information and current trends. This paper outlines the crisis communication research conducted at the ARC Centre of Excellence for Creative Industries and Innovation at Queensland University of Technology, and outlines the need for further background research into the longer-term development of social media platforms.

A Review of Social Media Analytics Tools

The next speaker at Digital Methods is Irmgard Wetzstein, whose interest is in social media monitoring tools. Social media monitoring is an increasingly important research area, of course, in both scholarly and commercial research, as the rise of 'big data' demonstrates. A social media monitoring industry has now emerged, providing a range of tools and services across various platforms. There are even systematic evaluations of the various tools, documenting this diversity.

If many such tools have emerged from commercial contexts, are they nonetheless also useful for scholarly purposes? Irmgard's study examined some 100 tools, focussing on tools which provide analytics for multiple social media platforms, and examined them across a range of parameters. Most of these tools are from the US or Canada, and focus on English-language content and user interfaces; largely, they focus on consumer, customer, and brand relations, but often offer broader thematic analysis, too.

#aufschrei: How a Hashtag Public Forms

The final paper in this Digital Methods panel is by Axel Maireder and Stefan Schlögl, whose interest is in the #aufschrei discussion about sexism in German politics. How did this emerge from a small-scale conversation on Twitter to a major trending hashtag, and subsequently to a cross-media event, over the course of a few hours? What happened here was the growth of a communicative network in the form of a partial public or issue public related to the topic on Twitter, interleaved with other publics as enabled by the conventional mainstream media.

New forms of discussion fora and spaces, especially also including social media, enable new and lasting connections between themes and individuals. These connections are increasingly manifested in the data structures which are available through social media APIs, too, and structure the flow of communication. URLs shared in tweets and other social media updates further document the connection of such communication with other, external media, while hashtags enable the development of ad hoc publics independent of existing follower networks.

How Julia Gillard's Misogyny Speech Went Viral

The next panel at the Digital Methods conference begins with a panel by Theresa Sauter and me, on the viral distribution of links to the video of Julia Gillard's "misogyny" speech in 2012 as it was posted in full on the ABC News site. Unfortunately the audio recording didn't work out, so below are the slides only - do make sure you click on the links to see the video and the animations of the emerging retweet network.

The Opportunities and Challenges of 'Big Data' Research

At the end of an extended trip to a range of conferences and symposia I've made my way to Vienna, where I'm attending the DGPuK Digital Methods conference at the University of Vienna. The conference is in German, but I'll try to blog the presentations in English nonetheless - wish me luck... We begin with keynote by Jürgen Pfeffer, addressing - not surprisingly - the question of 'big data' in communications research.

Jürgen begins by asking what's different about 'big data' research. In our field, we're using 'big data' on communication and interaction to work towards a real-time analysis of large-scale, dynamic sociocultural systems, necessarily especially through computational approaches - this draws on the data available from major social networks and other participative sites, but it aims not to research "the Internet", but society by examining communication patterns on the Internet (and elsewhere).

Distinguishing Chain and Name Networks in Social Network Analysis

The final speaker in this "Compromised Data" session is Anatoliy Gruzd, whose interest is in the automated discovery and visualisation of communication networks from social media data. (He's also just launched a new journal in this field, Big Data and Society.) How can such networks be discovered and visualised, and how can we evaluate the sense of community which may exist in them?

Social network analysis enables us to investigate the connections between users in social networks. It reduces large quantities of messages to a smaller number of nodes exchanging communication; it can track longitudinal developments over time; it can show the social dynamics of interaction around specific topics and events; and it can differentiate between different types of network formation in social interaction.

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