[Air-L] CFP: Understanding the spread of misinformation in the Australian and US media fields
Robert Ackland
robert.ackland at anu.edu.au
Tue Apr 10 04:35:23 PDT 2018
<on behalf of mathieu.oneil at canberra.edu.au> <apologies for multiple posts>
*CFP: Understanding the spread of misinformation in the Australian and
US media fields*
****
*Concepts and Methods Symposium*
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**News & Media Research Centre
University of Canberra
Friday 7 September 2018
*Networked misinformation*
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**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*
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**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 at 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*
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**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*
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**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
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