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'Big Data'

Does 'Fake News' Travel Faster than 'Real News'? (Spoiler: No.)

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.

News Diffusion on Twitter: Comparing the Dissemination Careers for Mainstream and Marginal News (SM&S 2020)

Social Media & Society 2020

News Diffusion on Twitter: Comparing the Dissemination Careers for Mainstream and Marginal News

Axel Bruns and Tobias Keller

Current scholarly as well as mainstream media discussion expresses substantial concerns about the influence of ‘problematic information’ from hyperpartisan and down

Homebrew CommResearch Club: Computational Approaches to Studying COVID-19 (CCA 2020)

CCA Solidarity Symposium 2020

Homebrew CommResearch Club: Computational Approaches to Studying COVID-19

Jonathan Zhu, Axel Bruns, Wenhong Chen, Cuihua Cindy Shen, Celine Yunya Song, and Wayne Xu

Homebrew Comm-Research is gaining momentum while we work from home. What are the basic approaches of computational communication research that may help combat the pandemic?

Do Music Managers Trust Streaming Metrics?

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.

Do Scholars Trust Their Altmetrics?

The next speaker in this AoIR 2019 session is my colleague Kim Osman, presenting outcomes from our research project in collaboration with The Conversation and the Cooperative Research Centres Association in Australia. We are interested in assessments of the public value and impact of scholarly work, which are also increasingly demanded by the governments that fund scholarly research. Slides here:

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