Literature DB >> 33837145

Measuring the news and its impact on democracy.

Duncan J Watts1,2,3, David M Rothschild4, Markus Mobius5.   

Abstract

Since the 2016 US presidential election, the deliberate spread of misinformation online, and on social media in particular, has generated extraordinary concern, in large part because of its potential effects on public opinion, political polarization, and ultimately democratic decision making. Recently, however, a handful of papers have argued that both the prevalence and consumption of "fake news" per se is extremely low compared with other types of news and news-relevant content. Although neither prevalence nor consumption is a direct measure of influence, this work suggests that proper understanding of misinformation and its effects requires a much broader view of the problem, encompassing biased and misleading-but not necessarily factually incorrect-information that is routinely produced or amplified by mainstream news organizations. In this paper, we propose an ambitious collective research agenda to measure the origins, nature, and prevalence of misinformation, broadly construed, as well as its impact on democracy. We also sketch out some illustrative examples of completed, ongoing, or planned research projects that contribute to this agenda.

Keywords:  democracy; media; misinformation

Year:  2021        PMID: 33837145     DOI: 10.1073/pnas.1912443118

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  3 in total

1.  Protecting infrastructure performance from disinformation attacks.

Authors:  Saeed Jamalzadeh; Kash Barker; Andrés D González; Sridhar Radhakrishnan
Journal:  Sci Rep       Date:  2022-07-26       Impact factor: 4.996

2.  Aggressive behaviour of anti-vaxxers and their toxic replies in English and Japanese.

Authors:  Kunihiro Miyazaki; Takayuki Uchiba; Kenji Tanaka; Kazutoshi Sasahara
Journal:  Humanit Soc Sci Commun       Date:  2022-07-05

3.  Deepfake detection by human crowds, machines, and machine-informed crowds.

Authors:  Matthew Groh; Ziv Epstein; Chaz Firestone; Rosalind Picard
Journal:  Proc Natl Acad Sci U S A       Date:  2022-01-04       Impact factor: 11.205

  3 in total

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