<on behalf of mathieu.oneil@canberra.edu.au> <apologies for multiple posts> *CFP: Understanding the spread of misinformation in the Australian and US media fields* **** *Concepts and Methods Symposium* **** **News & Media Research Centre University of Canberra Friday 7 September 2018 *Networked misinformation* **** **Growing fragmentation in media systems has resulted in dramatically increased choice for media consumers. This process has been accelerated by the growth of digital platforms for news and information which open media spaces not only to a wider diversity of outlets but also to foreign and domestic information operations: strategic actors can sow disinformation relatively covertly, distancing their activities from their foreign or domestic patrons. We distinguish misinformation - the accidental statement of factually incorrect claims - from disinformation, which is strategic or intentional. To what extent are these activities enabled by the affordances of social media such as 'echo chambers' (media environments where people only connect with like-minded others) and 'filter bubbles' (resulting from media content being algorithmically selected to match previous consumer choices)? There has been much empirical debate as to the existence of echo chambers and filter bubbles. To the extent they exist, both phenomena result in media consumers being exposed to information that reinforces previously held beliefs. The disappearance of attitude-challenging content and attendant rise of misinformed opinion is thought to have played a role in the 2016 US Presidential election, where information untethered to reality (see for example ‘Pizzagate’) spread amongst some Republican Party supporter networks. Whether they are used by strategic actors seeking to achieve political objectives or not, echo chambers and filter bubbles challenge the functioning of the news media as a public sphere where the informed confrontation of contrasting viewpoints can lead to common understanding and agreement about what exists, and what matters. The consequences are profound: we may be arriving at a cultural moment where a significant part of the population no longer believes that facts are knowable. *Symposium aims and submissions* **** **Are echo chambers and filter bubbles real? If they are real, to what extent do they contribute to the spread of misinformation? Are ‘filter-bursting’ strategies available? What’s it like in there, anyway? Are journalists part of the problem, or are they the solution? If journalists in the US and UK failed to anticipate Brexit and the election of Donald Trump because of filter bubbles and echo chambers, is the Australian journalistic field similarly afflicted? The Understanding the spread of misinformation in the Australian and US media fields Symposium will bring together journalists and researchers, cutting-edge computational methods and first-hand accounts of actors in the field, to assess to what extent filter bubbles and echo chambers contribute to the spread of misinformation. Please send 500-word abstract of presentations to *mathieu.oneil@canberra.edu.au* by 31 May 2018. Suitable presentations will be invited to contribute to a journal special issue. Researchers and journalists are encouraged to address questions including, but not limited to: *Are there echo chambers, filter bubbles and fake-news spreading hubs in the Australian media field? *Comparative approaches: misinformation and disinformation in the Australian and US media fields, and beyond. *How are foreign or domestic strategic actors using media spaces and to what extent and through what mechanisms are they impacting news reporting? *Is Australia at risk of being swamped by ‘fake news’? Why or why not? *Bubbles in the eye of the beholder: when does a belief become a conspiracy? *Do the specific features of the Australian media field (duopolistic structure, late arrival of Cable News, public broadcasting) affect the spread of misinformation? *What steps are journalists taking to counter the impact of social media on meaningful democratic deliberation? *How can confirmation bias (biased information confirming previously held beliefs as plausible) be addressed? *Is the rejection of professional journalism and expertise, common among populists who have emerged in response to neoliberalism, limited to certain sectors of the ideological spectrum? Why or why not? *Does focusing on algorithmic filtering obscures other processes detrimental to democratic politics? Additional factors may have played a key role in the 2016 US election, such as the manipulation of recommendation systems through the exploitation of so-called ‘click-workers’ and ‘like farms’, often located in poor countries (Casilli, 2016). In 2015 it was estimated that 58% of the accounts which ‘liked’ Donald Trump’s Facebook page were fake, for example (Brown, 2015). *Organising committee* **** **Mathieu O’Neil, News & Media Research Centre, University of Canberra Michael Jensen, Institute for Policy and Governance Analysis, University of Canberra Robert Ackland, Virtual Observatory for the Study of Online Networks (VOSON) Lab, Australian National University Amy Remeikis, Political Reporter, The Guardian Australia *Background* **** **The loss of a common political discourse resulting from a fragmenting of the online population into narrowly-focused groups of individuals solely exposed to information confirming previously held opinions and biases was first referred to as ‘echo chambers’ by Sunstein (2001) whilst Van Alstyne & Brynjolfsson (2005) described a process of ‘cyber-balkanisation’. This fragmentation facilitates the seeding of misinformation by strategic actors to sympathetic audiences, who are more likely to believe claims not on the basis of factual predicates, but on that of their resonance to their identity (Miskimmon et al. 2013, Benkler et al. 2017). However, while the concept of the filter bubble is widespread, there is scant empirical evidence for the existence and impact of filter bubbles with many researchers simply assuming that filter bubbles exist, and that something needs to be done about them. Filter bubbles almost bear the hallmarks of a ‘moral panic’, with social scientists, computer scientists and engineers vying to provide solutions to a phenomenon that is yet to be properly explored and understood. The limited research that is relevant to filter bubbles has tended to involve either surveys of social media users (‘where do you get your news?’) or analysis of ‘big data’ collected unobtrusively from social media. Big data studies and network analysis tend to provide support for the filter bubble thesis while survey-based research tends to discount it. Nielsen (2016) uses data from the 2015 Reuters Institute Digital News Report to argue that ‘social media users in fact use significantly more different sources of news than non-users’. Similarly, a more recent study reveals that social media use tend to diversify news consumers’ diet rather than narrow it (Fletcher & Nielsen, 2017). The research on the drivers of networked misinformation such as echo chambers and filter bubbles can be advanced in several ways. First, this research usually pertains to the perils posed by online echo chambers to general users. Less attention has been paid to how such phenomena, when operating in influential sectors of society such as the journalistic field, can be detrimental to the plural public discourse that is essential to democracy. Second, this research deals with very general notions such as ‘the Internet’, ‘social media’, or ‘Twitter’, obviating the fact that not only are there ‘online spaces which develop distinctive and well-ordered cultures’ (Hine 2015: 38), but that these online spaces are frequently embedded in highly distinctive offline locales. Finally, research on filter bubbles has tended to eschew consideration of a key behaviour that contribute to these phenomena: how people engage with news. *References* **** **Benkler, Y., Faris, R., Roberts, H., & Zuckerman, E. (2017). Study: Breitbart-led right-wing media ecosystem altered broader media agenda. Columbia Journalism Review, March 3. Brown, J. (2015). There's something odd about Donald Trump's Facebook page. Business Insider, June 18. <http://www.businessinsider.com/donald-trumps-facebook-followers-2015-6?IR=T> Casilli, A. (2016). Never mind the algorithms: the role of exploited digital labor and global click farms in Trump’s election. <http://www.casilli.fr/2016/11/20/never-mind-the-algorithms-the-role-of-exploited-digital-labor-and-global-click-farms-in-trumps-election/> Fletcher, R. & Nielsen, R.K. (2017). Using social media appears to diversify your news diet, not narrow it. Nieman Lab. <http://www.niemanlab.org/2017/06/using-social-media-appears-to-diversify-your-news-diet-not-narrow-it/> Hine, C. (2015). Ethnography for the Internet. London: Bloomsbury Academic. Menczer, F. (2017). Misinformation on social media: Can technology save us? The Conversation. <http://theconversation.com/misinformation-on-social-media-can-technology-save-us-69264> Miskimmon, A., O'Loughlin, B., & Roselle, L. (2013). Strategic Narratives: Communication Power and the New World Order. Routledge, New York. Nielsen, R. K. (2016). <https://rasmuskleisnielsen.net/2016/11/25/is-social-media-use-associated-with-more-or-less-diverse-news-use/> Pariser, E. (2011). The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think, Penguin Press. Sunstein, C. (2001). Republic.com. Princeton University Press, Princeton. Van Alstyne, M. & Brynjolfsson, E. (2005). Global village or cyber-balkans? Modeling and measuring the integration of electronic communities. Management Science, 51, 851–868. -- Dr Robert Ackland Associate Professor, School of Sociology Leader, Virtual Observatory for the Study of Online Networks (VOSON) Lab <http://vosonlab.net> The Australian National University