Without in-person conferences to liveblog, this site has been a little quiet recently. But that doesn’t mean that there isn’t any news to report – so here is the first of a number of posts with updates on recent activities. First of all, I’m very pleased that a number of articles I’ve contributed to have finally been published over the past few months – and in particular, that they represent the results of a range of collaborations with new and old colleagues.

The first of these is a new book chapter led by my QUT Digital Media Research Centre colleague and former PhD student Ehsan Dehghan, which provides a useful update on his and our current approach to discourse analysis. Building on Ehsan’s work for his excellent PhD thesis, the book chapter connects a detailed methodological overview with the conceptual approaches of Laclau and Mouffe, exploring the presence of agonistic and antagonistic tendencies across a number of case studies. The chapter was published in the third volume in Rebecca Lind’s Produsing Theory book series, which in its title also draws on my concept of produsage, of course.

Dehghan, Ehsan, Axel Bruns, Peta Mitchell, and Brenda Moon. “Discourse-Analytical Studies on Social Media Platforms: A Data-Driven Mixed-Methods Approach.” Produsing Theory in a Digital World 3.0, ed. Rebecca Ann Lind. New York: Peter Lang, 2020. 159–77. DOI:10.3726/b13192/20.

A second new article results from another collaboration with a former PhD student, Felix Münch, now a postdoctoral researcher at the Hans-Bredow-Institut in Hamburg. Building on the work Felix presented at the 2019 AoIR Flashpoint Symposium in Urbino, this article in Social Media + Society outlines a new approach to mapping the network structure of a national Twittersphere, offering a pathway towards generating some critically important baseline data against which observations from hashtag- and keyword-based studies may be compared.

Münch, Felix Victor, Ben Thies, Cornelius Puschmann, and Axel Bruns. “Walking through Twitter: Sampling a Language-Based Follow Network of Influential Twitter Accounts.” Social Media + Society 7.1, (2021) DOI:10.1177/2056305120984475.

Third, I’m also very pleased to have made a contribution to a new article in Digital Journalism by Magdalena Wischnewski, a visiting PhD scholar supported by the RISE-SMA research network coordinated by Stefan Stieglitz at the University of Duisburg-Essen. Caught up in the travel disruptions caused by the COVID-19 pandemic, Magdalena spent rather more time with us at the QUT DMRC than we had planned, but happily we were able to put this extra time to good use and investigate the motivations for sharing hyper-partisan content (in this case study, from InfoWars) on Twitter.

The COVID-19 online edition of the wonderful Social Media & Society conference has just started, and my colleague Tobias Keller and I are presenting our latest research via a YouTube video that has now been released. In our study we examine the average dissemination curves for news articles from mainstream and fringe news sources; this analysis is prompted by the persistent media framing of past research as (supposedly) showing that ‘fake news’ disseminates more quickly than ‘real news’.

Leaving aside such disputed labels, we find no evidence of any systematic differences in dissemination speeds on Twitter: during 2019, for example, stories from the Australian Broadcasting Corporation’s ABC News site (Australia’s most trusted news source) disseminated almost exactly as quickly as those from the hyperpartisan outlet Breitbart: on average, both reached 25% of their eventual dissemination within just under four hours, and 50% after ten hours.

There are, though, notable differences between different site types: content from specialist sites like The Conversation (which publishes scholarly findings and commentary for a general audience) or Judicial Watch (engaging in hyperpartisan legal commentary and lawfare) usually disseminates considerably more slowly than material from more generalist news sites, from the mainstream or the fringes.

Here are the video and slides from our presentation – and a work-in-progress paper (though focussing on only one month of data, rather than all of 2019) is also online.

The final speaker in this AoIR 2019 session is Arnt Maasø, who shifts our attention to the role of metrics in the music business. Datafication has grown in the music industry as well, with a strong turn to metrics in recent years. Where some decades ago the industry was run by self-taught entrepreneurs who were running their businesses predominantly by gut instinct, now music metrics are everywhere and directly influence decision-making.