Cited by 305Complex Network Analysis TechniquesMisinformation and Its ImpactsSocial Media and Politics

Anatomy of news consumption on Facebook

Open access
Schmidt, Ana Lucía, Zollo, Fabiana, Del Vicario, Michela, Bessi, Alessandro, Scala, Antonio, Caldarelli, Guido, Stanley, H. Eugene, Quattrociocchi, Walter·2017·Proceedings of the National Academy of Sciences

Abstract

Significance: Social media heavily changed the way we get informed and shape our opinions. Users’ polarization seems to dominate news consumption on Facebook. Through a massive analysis on 920 news outlets and 376 million users, we explore the anatomy of news consumption on Facebook on a global scale. We show that users tend to confine their attention on a limited set of pages, thus determining a sharp community structure among news outlets. Furthermore, our findings suggest that users have a more cosmopolitan perspective of the information space than news providers. We conclude with a simple model of selective exposure that well reproduces the observed connectivity patterns.

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Registry

Crossref · 10.1073/pnas.1617052114

Cites

27 of 27 references verified0 citation errors · 0 not checkable

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  • Feed algorithms might limit our selection process by suggesting contents similar to the ones we are usually exposed to.

    “Our attention span remains limited (9, 10), and feed algorithms might limit our selection process by suggesting contents similar to the ones we are usually exposed to (11–13).”

    From The echo chamber effect on social media (2021) · cites this paper as [11]

  • Online media has become a widespread source of information and opinion formation.

    “With the advent of the Internet, online media has become a widespread source of information and, subsequently, opinion formation5–9.”

    From Negativity drives online news consumption (2023) · cites this paper as [6]

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Authors
Schmidt, A. L., Zollo, F., Del Vicario, M., Bessi, A., Scala, A., Caldarelli, G., Stanley, H. E., & Quattrociocchi, W.
Affiliations
  • IMT School for Advanced Studies Lucca (IT)
  • Laboratory of Computational Social Science, Networks Department, IMT Alti Studi Lucca, 55100 Lucca, Italy;
  • Istituto Universitario di Studi Superiori di Pavia (IT)
  • Department of Physics, Boston University, Boston, MA 02115
Venue
Proceedings of the National Academy of Sciences
Published
2017-03-06
Volume
114
Issue
12
Pages
3035-3039
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2594227947
Cited by
305
References
27
Citations by year
2026: 11 · 2025: 32 · 2024: 26 · 2023: 36 · 2022: 35 · 2021: 48 · 2020: 45 · 2019: 33 · 2018: 26 · 2017: 10 · 2016: 2
FWCI
16.18
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
  • ARCA (Università Ca' Foscari Venezia) (submittedVersion, other-oa)
Topics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Social Sciences › Communication › Social Media and Politics
Keywords
news consumption, Facebook, social media, selective exposure, user preferences, geolocation, information space, opinion formation

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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.

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