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Abstract

In studies of misinformation, the distinction between high- and low-credibility publishers is fundamental. However, there is much that we do not know about the relationship between the subject matter and timing of content produced by the two types of publishers. By analyzing the content of several million unique articles published over 28 months, we show that high- and low-credibility publishers operate in distinct news ecosystems. Bursts of news coverage generated by the two types of publishers tend to cover different subject matter at different times, even though fluctuations in their overall news production tend to be highly correlated. Regardless of the mechanism, temporally convergent coverage among low-credibility publishers has troubling implications for American news consumers.

Keywords

Agenda-setting misinformation network analysis news cycle news production online news

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References

Adamic

Glance

(2005) The political blogosphere and the 2004 U.S. election: divided they blog. Available at: https://doi.org/10.1145/1134271.1134277

Allcott

Gentzkow

(2017) Social media and fake news in the 2016 election. Journal of Economic Perspectives 31(2): 211–236.

Allcott

Gentzkow

(2018) Trends in the diffusion of misinformation on social media. Available at: https://journals.sagepub.com/doi/full/10.1177/2053168019848554#:~:text=User%20interactions%20with%20false%20content,Twitter%20shares%20decreasing%20by%2060%25

Allen

Howland

Mobius

, et al. (2020) Evaluating the fake news problem at the scale of the information ecosystem. Science Advances 6(14): eaay3539.

Benkler

Faris

Roberts

(2018) Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics. Oxford: Oxford University Press.

Boczkowski

de Santos

(2007) When more media equals less news: patterns of content homogenization in Argentina’s leading print and online newspapers. Political Communication 24(2): 167–180.

Bovet

Makse

(2019) Influence of fake news in Twitter during the 2016 US presidential election. Nature Communications 10(1): 7.

Bozarth

Budak

(2020) Toward a better performance evaluation framework for fake news classification. Available at: https://ojs.aaai.org/index.php/ICWSM/article/view/7279

Budak

(2019) What happened? The spread of fake news publisher content during the 2016 U.S. presidential election. Available at: https://dl.acm.org/doi/10.1145/3308558.3313721

10.

Buhl

Günther

Quandt

(2018) Observing the dynamics of the online news ecosystem. Journalism Studies 19(1): 79–104.

11.

Chadwick

(2011) The political information cycle in a hybrid news system: the British prime minister and the “Bullygate” affair. The International Journal of Press/Politics 16(1): 3–29.

12.

Couts

Wyrich

(2017) Here are all the “fake news” sites to watch out for on Facebook. Available at: https://www.dailydot.com/layer8/fake-news-sites-list-facebook/

13.

Cushion

(2019) News cycle. In: Vos

Hanusch

(eds) The International Encyclopedia of Journalism Studies. Hoboken, NJ: John Wiley & Sons, pp. 1–4.

14.

Cushion

Kilby

Thomas

, et al. (2018) Newspapers, impartiality and television news. Journalism Studies 19(2): 162–181.

15.

De Solla Price

(1963) Invisible Colleges and the Affluent Scientific Commuter. New York: Columbia University Press.

16.

Eldridge

(2019a) “Thank god for Deadspin”: interlopers, metajournalistic commentary, and fake news through the lens of “journalistic realization.” New Media & Society 21(4): 856–878.

17.

Eldridge

(2019b) Where do we draw the line? Interlopers, (Ant)agonists, and an unbounded journalistic field. Media and Communication 7(4): 8–18.

18.

Elswah

Howard

(2020) “Anything that causes chaos”: the organizational behavior of Russia Today (RT). Journal of Communication 70(5): 623–645.

19.

Frank

(2003) ‘These crowded circumstances’: when pack journalists bash pack journalism. Journalism 4(4): 441–458.

20.

Geiß

(2022) The media’s conditional agenda-setting power: how baselines and spikes of issue salience affect likelihood and strength of agenda-setting. Communication Research 49(2): 296–323.

21.

Gomez-Rodriguez

Leskovec

Krause

(2012) Inferring networks of diffusion and influence. ACM Transactions on Knowledge Discovery from Data 5(4): 37. DOI: 10.1145/2086737.2086741.

22.

Grinberg

Joseph

Friedland

, et al. (2019) Fake news on Twitter during the 2016 U.S. presidential election. Science 363(6425): 374–378.

23.

Guess

Nagler

Tucker

(2019) Less than you think: prevalence and predictors of fake news dissemination on Facebook. Science Advances 5(1): eaau4586.

24.

Guess

Lyons

(2020) Misinformation, disinformation, and online propaganda. In: Persily

Tucker

(eds) Social Media and Democracy: The State of the Field, Prospects for Reform. Cambridge: Cambridge University Press, pp. 10–33.

25.

Guess

Nyhan

Reifler

(2020) Exposure to untrustworthy websites in the 2016 US election. Nature Human Behaviour 4(5): 472–480.

26.

Guo

Vargo

(2020) “Fake news” and emerging online media ecosystem: an integrated intermedia agenda-setting analysis of the 2016 US presidential election. Communication Research 47(2): 178–200.

27.

Harcup

O’Neill

(2017) What is news? Journalism Studies 18(12): 1470–1488.

28.

Harder

Sevenans

Van Aelst

(2017) Intermedia agenda setting in the social media age: how traditional players dominate the news agenda in election times. The International Journal of Press/Politics 22(3): 3.

29.

Hassell

HJG

(2021) What makes news newsworthy: an experimental test of where a news story is published (or not) and its perceived newsworthiness. The International Journal of Press/Politics 26(3): 654–673.

30.

Hendrickx

(2020) Trying to survive while eroding news diversity: legacy news media’s catch-22. Journalism Studies 21(5): 598–614.

31.

Hopp

Fisher

Weber

(2020) Dynamic transactions between news frames and sociopolitical events: an integrative, hidden Markov model approach. Journal of Communication 70(3): 335–355.

32.

Kapantai

Christopoulou

Berberidis

, et al. (2021) A systematic literature review on disinformation: toward a unified taxonomical framework. New Media & Society 23(5): 1301–1326.

33.

Kleinberg

(1999) Hubs, authorities, and communities. ACM Computing Surveys 31(4es): 5–es.

34.

Klinenberg

(2005) Convergence: news production in a digital age. The ANNALS of the American Academy of Political and Social Science 597(1): 48–64.

35.

Kolitsas

Ganea

Hofmann

(2018) End-to-end neural entity linking. Available at: https://aclanthology.org/K18-1050/#:~:text=Entity%20Linking%20(EL)%20is%20an,without%20leveraging%20their%20mutual%20dependency

36.

Lazer

DMJ

Baum

Benkler

, et al. (2018) The science of fake news. Science 359(6380): 1094–1096.

37.

Leskovec

Backstrom

Kleinberg

(2009) Meme-tracking and the dynamics of the news cycle. Available at: https://doi.org/10.1145/1557019.1557077

38.

Bond

(2023) Examining semantic (dis)similarity in news through news organizations’ ideological similarity, similarity in truthfulness, and public engagement on social media: a network approach. Human Communication Research 49: 47–60.

39.

Lin

Margolin

Lazer

(2014) Tracing coordination and cooperation structures via semantic burst detection. Collaborative Computing 14(2): e7.

40.

Messing

State

Nayak

, et al. (2018) Facebook URL shares. Available at: https://doi.org/10.7910/DVN/EIAACS

41.

Newman

(2003) Mixing patterns in networks. Physical Review E 67(2): 026126.

42.

Paul

Matthews

(2016) The Russian “Firehose of Falsehood” Propaganda Model: Why It Might Work and Options to Counter It. Santa Monica, CA: RAND Corporation, p. 16.

43.

Pennycook

Cannon

Rand

(2018) Prior exposure increases perceived accuracy of fake news. Journal of Experimental Psychology: General 147(12): 1865–1880.

44.

PolitiFact (2017) Politifact’s guide to fake news websites and what they peddle. Available at: https://www.politifact.com/article/2017/apr/20/politifacts-guide-fake-news-websites-and-what-they/

45.

Rae

(2021) Hyperpartisan news: rethinking the media for populist politics. New Media & Society 23(5): 5.

46.

Reese

Danielian

(1989) Intermedia influence and the drug issue: converging on cocaine. In: Shoemaker

(ed.) Communication Campaigns about Drugs: Government, Media, and the Public. Mahwah, NJ: Lawrence Erlbaum Associates, pp. 29–46.

47.

Ryfe

(2006) Guest editor’s introduction: new institutionalism and the news. Political Communication 23(2): 135–144.

48.

Saridou

Spyridou

Veglis

(2017) Churnalism on the rise? Assessing convergence effects on editorial practices. Digital Journalism 5(8): 1006–1024.

49.

Schudson

(2001) The objectivity norm in American journalism. Journalism 2(2): 149–170.

50.

Shoemaker

Vos

(2009) Gatekeeping Theory. Abingdon-on-Thames: Taylor & Francis.

51.

Silverman

(2015) Lies, damn lies, and viral content: how news websites spread (and debunk) online rumors, unverified claims and misinformation. A Tow/Knight Report, Tow Center for Digital Journalism, New York.

52.

SimilarWeb (2022) Website traffic—check and analyze any website. Available at: https://www.similarweb.com/

53.

Tan

Friggeri

Adamic

(2021) Lost in propagation? Unfolding news cycles from the source. Available at: https://ojs.aaai.org/index.php/ICWSM/article/view/14712

54.

Vargo

Guo

Amazeen

(2018) The agenda-setting power of fake news: a big data analysis of the online media landscape from 2014 to 2016. New Media & Society 20(5): 2028–2049.

55.

Vos

Heinderyckx

(2015) Gatekeeping in Transition. Abingdon-on-Thames: Taylor & Francis.

56.

Vosoughi

Roy

Aral

(2018) The spread of true and false news online. Science 359(6380): 1146–1151.

57.

Watts

Dodds

(2007) Influentials, networks, and public opinion formation. Journal of Consumer Research 34(4): 441–458.

58.

Welbers

van Atteveldt

Kleinnijenhuis

, et al. (2016) News selection criteria in the digital age: professional norms versus online audience metrics. Journalism 17(8): 1037–1053.

59.

Wihbey

Joseph

Lazer

(2019) The social silos of journalism? Twitter, news media and partisan segregation. New Media & Society 21(4): 815–835.

60.

Wineburg

McGrew

(2019) Lateral reading: reading less and learning more when evaluating digital information. Teachers College Record 121(11): 1–40.

61.

Zandt

(2018) Media bias/fact check: MBFC news: about. Available at: https://mediabiasfactcheck.com/about/

62.

Zhang

Lukito

M-H

, et al. (2021) Assembling the networks and audiences of disinformation: how successful Russian IRA Twitter accounts built their followings, 2015–2017. Journal of Communication 71(2): 305–331.

63.

Zimdars

(2018) False, misleading, clickbait-y, and/or satirical “news” sources. Available at: https://docs.google.com/document/d/10eA5-mCZLSS4MQY5QGb5ewC3VAL6pLkT53V_81ZyitM/preview

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Bursts of contemporaneous publication among high- and low-credibility online information providers

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