Social Networking

Sharing without clicking on news in social media

Abstract

Social media have enabled laypersons to disseminate, at scale, links to news and public affairs information. Many individuals share such links without first reading the linked information. Here we analysed over 35 million public Facebook posts with uniform resource locators shared between 2017 and 2020, and discovered that such ‘shares without clicks’ (SwoCs) constitute around 75% of forwarded links. Extreme and user-aligned political content received more SwoCs, with partisans engaging in it more than politically neutral users. In addition, analyses with 2,969 false uniform resource locators revealed higher shares and, hence, SwoCs by conservatives (76.94%) than liberals (14.25%), probably because, in our dataset, the vast majority (76–82%) of them originated from conservative news domains. Findings suggest that the virality of political content on social media (including misinformation) is driven by superficial processing of headlines and blurbs rather than systematic processing of core content, which has design implications for promoting deliberate discourse in the online public sphere.

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Fig. 1: The relationship between political content affinity and affinity alignment with SwoCs of 4,617 top-shared domains.
Fig. 2: The relationship between content affinity and SwoCs of political and non-political URLs.
Fig. 3: Relationship between affinity alignment and SwoCs of political and non-political URLs.
Fig. 4: Shares and SwoCs of political and non-political URLs by five political user affinity groups.

Data availability

Access to Facebook data was granted via Social Science One, with all researchers in need of access to Facebook data signing a Research Data Agreement between Facebook, Inc. and the Grantee institution (Pennsylvania State University). Details about these data, including the codebook, can be found at the Social Science One Dataverse repository at https://socialscience.one/facebook-dataverse.

Code availability

Researchers were allowed special access to a JupyterHub system that provides an interface to query the data. Information to obtain authentication and access to JupyterHub, as well as resources for data analysis, was communicated through an invite-only GitHub organization (https://github.com/fb-researchtool-ss1). All data were retrieved, prepared and analysed via Python programming language (version 3.10.11) with the following packages: NLTK (version 3.8.1) and scikit-learn (version 1.2.2). Examples of major Python codes used for data retrieval, preparation and analysis can be found via GitHub at https://github.com/geocomplexity/SwoCMetaURL.

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Acknowledgements

This research was supported by Social Media and Democracy Research Grants, awarded by the Social Science Research Council, with access to Facebook data via Social Science One (grantees: S.S.S., G.C., J.W. and J.Y.). The grants are funded by a group of charitable foundations including the Laura and John Arnold Foundation, the Children’s Investment Fund Foundation, the Democracy Fund, the William and Flora Hewlett Foundation, the John S. and James L. Knight Foundation, the Charles Koch Foundation, Omidyar Network and the Alfred P. Sloan Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. See more information about the grant project at https://www.ssrc.org/grantees/are-we-more-willing-to-speak-up-when-we-share-without-clicking-a-study-of-political-content-sharing-on-facebook/.

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Authors and Affiliations

  1. Donald P. Bellisario College of Communications, Pennsylvania State University, University Park, PA, USA

    S. Shyam Sundar

  2. Department of the Humanities and Social Sciences, New Jersey Institute of Technology, Newark, NJ, USA

    Eugene Cho Snyder

  3. Grady College of Journalism and Mass Communication, University of Georgia, Athens, GA, USA

    Mengqi Liao

  4. Social Science Research Institute and Population Research Institute, Pennsylvania State University, University Park, PA, USA

    Junjun Yin & Guangqing Chi

  5. College of Journalism and Communications, University of Florida, Gainesville, FL, USA

    Jinping Wang

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Contributions

Conceptualization: S.S.S., E.C.S., M.L., J.Y., J.W. and G.C. Methodology: S.S.S., E.C.S., M.L., J.Y., J.W. and G.C. Investigation: S.S.S., E.C.S., M.L., J.Y., J.W. and G.C. Data wrangling: E.C.S., J.Y. and M.L. Visualization: E.C.S., M.L., S.S.S. and J.Y. Funding acquisition: S.S.S., J.Y., J.W. and G.C. Project administration: S.S.S. and E.C.S. Supervision: S.S.S. Writing—original draft: S.S.S., E.C.S., M.L. and J.Y. Writing—review and editing: S.S.S., E.C.S., M.L., J.Y., J.W. and G.C.

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Correspondence to
S. Shyam Sundar.

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Nature Human Behaviour thanks Porismita Borah, Daniel Muise and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 SwoCs and shares of political URLs rated as false (left) and true (right) news by five political affinity groups.

While hardly visible, error ticks are applied to account for noise embedded to shares (σ = 14) and shares without clicks (σ = 10)). σ is a noise parameter calculated by Meta for each user action, including shares and shares without clicks.

Extended Data Fig. 2 Distribution of domain-level content affinity.

Distribution of all 4,617 domains (left), 817 domains with AllSides media bias ratings assigned (middle), and 2,636 domains with Robertson et al.’s (33) media scores assigned (right).

Extended Data Fig. 3 Relationship between domain-level content affinity and SwoCs among domains with external ratings of media bias.

Data based on AllSides (left) and Robertson et al.’s (33) (right) ratings.

Extended Data Fig. 4 Relationship between domain-level affinity alignment and SwoCs among domains with external ratings of media bias.

Data based on AllSides (left) and Robertson et al.’s (33) (right) ratings.

Extended Data Fig. 5 SwoCs and shares of fact-checked political URLs from media sources rated by AllSides.

Data for false (left) and true (right).

Supplementary information

Supplementary Information

Supplementary Data Tables 1–12.

Reporting Summary

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Sundar, S.S., Snyder, E.C., Liao, M. et al. Sharing without clicking on news in social media.
Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-02067-4

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