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Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics
Open accessAbstract
This book examines the shape, composition, and practices of the United States political media landscape. It explores the roots of the current epistemic crisis in political communication with a focus on the remarkable 2016 U.S. president election culminating in the victory of Donald Trump and the first year of his presidency. The authors present a detailed map of the American political media landscape based on the analysis of millions of stories and social media posts, revealing a highly polarized and asymmetric media ecosystem. Detailed case studies track the emergence and propagation of disinformation in the American public sphere that took advantage of structural weaknesses in the media institutions across the political spectrum. This book describes how the conservative faction led by Steve Bannon and funded by Robert Mercer was able to inject opposition research into the mainstream media agenda that left an unsubstantiated but indelible stain of corruption on the Clinton campaign. The authors also document how Fox News deflects negative coverage of President Trump and has promoted a series of exaggerated and fabricated counter narratives to defend the president against the damaging news coming out of the Mueller investigation. Based on an analysis of the actors that sought to influence political public discourse, this book argues that the current problems of media and democracy are not the result of Russian interference, behavioral microtargeting and algorithms on social media, political clickbait, hackers, sockpuppets, or trolls, but of asymmetric media structures decades in the making. The crisis is political, not technological.
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“In response, communication scholars have adopted decades-old theories of propaganda and mass communication to understand disinformation and media manipulation online (154, 159, 160).”
From Stewardship of global collective behavior (2021) · cites this paper as [154]
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“This raises the possibility that some business models may be fundamentally incompatible with a healthy society (154).”
From Stewardship of global collective behavior (2021) · cites this paper as [154]
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“That is, we can see how decoupling from the broader media ecosystem—which is not (yet) happening among left-leaning social media (Benkler et al. 2018; Freelon et al. 2020)2—confers some advantages for instigating offline social action.”
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“So while the causes and consequences of disinformation is being constructed as a public problem eliciting considerable concern, several notable studies have cautioned that it should not be over-inflated in terms of its “real-world” social and political impacts (Benkler et al., 2018).”
BackgroundBelieving and Sharing Information by Fake Sources: An Experiment
Bauer, P. C., & von Hohenberg, B. C. (2020) · Political Communication · doi:10.1080/10584609.2020.1840462 · Cited by 52
“In contrast to observational studies in the US (e.g., Benkler et al., 2018), we do not find any clear patterns in partisan sharing behavior (see Appendix A.7).”
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Varanasi, R. A., Pal, J., & Vashistha, A. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517588 · Cited by 46
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“In conjunction, and perhaps inspired by Roberts’ use of the term, it has featured in several academic articles concerned with the same issue (Kreiss, 2019; Benkler et al., 2018; Crawford, 2019; Ellis, 2020; Steensen, 2019).”
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“Missinformationen) einen nicht unerheblichen Anteil an Shares auszumachen (Allcott und Gentzkow 2017; Benkler et al. 2018).”
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“Benkler et al., 2018 found a tightly interwoven and deeply ideological right-wing media space relatively disconnected from other media; the media spaces occupied by the center and on the left were more loosely interlinked.”
BackgroundA Survey on the Use of Graph Convolutional Networks for Combating Fake News
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“Similar to Benkler et al. (2018), we call this post-truth 1Akademische Rätin, University of Augsburg, Augsburg, Germany 2Associate Professor, North Carolina State University, Raleigh, NC, USA Corresponding Author: Chad Hoggan, Associate Professor, North Carolina State University, Campus Box 7801,…”
MethodInterdisciplinary Lessons Learned While Researching Fake News
Sample, C., Jensen, M. J., Scott, K. M., McAlaney, J., Fitchpatrick, S., Brockinton, A., Ormrod, D., & Ormrod, A. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.537612 · Cited by 38
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“The conservative media ecosystem is more susceptible to disinformation operations (Benkler et al. 2018).”
BackgroundKim, J. W., & Chen, G. M. (2020) · Journalism Practice · doi:10.1080/17512786.2020.1739550 · Cited by 33
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“Not only do we need intensive studies of how partisan sites drive the political agenda by infusing false information into democratic debates (Benkler et al., 2018), but research needs to more deeply examine the intersection between agenda- and frame-building in the construction of political agendas.”
BackgroundBennett, W. L., & Livingston, S. G. (2023) · Springer studies in media and political communication · doi:10.1007/978-3-031-45335-9_4 · Cited by 34
A God-Tier LARP? QAnon as Conspiracy Fictioning
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“…conspiracy movements has focused on the role of social media platforms in facilitating and amplifying their spread: the rabbit holes created by YouTube’s recommendation algorithms (Lewis, 2020), Facebook’s filter bubbles, and Twitter’s echo chambers (Benkler et al., 2018; Phillips & Milner, 2021).”
BackgroundMetrics in action: how social media metrics shape news production on Facebook
Mukerjee, S., Tian, Y., & Peng, Y. (2023) · Journal of Communication · doi:10.1093/joc/jqad012 · Cited by 44
Metadata
- Authors
- Benkler, Y., Faris, R., & Roberts, H.
- Affiliations
- Harvard University (US)
- Publisher
- Oxford University PressNew York
- Published
- 2018-10-18
- OpenAlex
- W4213327489
- Cited by
- 1,504
- References
- 0
- Citations by year
- 2026: 269 · 2025: 260 · 2024: 206 · 2023: 198 · 2022: 165 · 2021: 173 · 2020: 172 · 2019: 59 · 2018: 1
- FWCI
- 116.61
- Type
- book
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BiblioBoard Library Catalog (Open Research Library) (submittedVersion, cc-by-nc-nd)
- Directory of Open access Books (OAPEN Foundation) (submittedVersion, cc-by)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Communication › Social Media and Politics
- Keywords
- 2016 US presidential election, Donald Trump, disinformation, media polarization, conservative media, Steve Bannon, Fox News, Mueller investigation, counter-narratives, media and democracy, public sphere
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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