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Social Media and Trust in News: An Experimental Study of the Effect of Facebook on News Story Credibility
Open accessAbstract
People increasingly turn to social media to get their daily news updates. Still, we are only beginning to understand how this development affects people’s perceptions of consumed news stories. The article reports on an experiment designed to investigate the effect the distribution of a news story in social media (Facebook) has on news message credibility. A control group was exposed to a news story on an original news website, and treatment groups were exposed to the same news story shared on Facebook. Results demonstrate that distribution via Facebook affects the credibility of the news story. The effect is strongest when politicians are intermediary-senders, and to some extent depend on the party affiliation of intermediary-sender and the social media audience. In the context of fake news, the results are reassuring: people are less trustful of news they consume through social media. However, the results also suggest that social media news sharing can contribute to the long-term decrease in trust in news.
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“Results from two studies suggest that personal political ideology or political afliation infuences participants' trust in information from social media [5,53].”
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“Users recognize them, classify them ideologically, and thereby reduce the cognitive cost of politically evaluating the content and information they produce (Alsaad et al., 2021; Karlsen and Aalberg, 2021; Mosleha et al., 2021).”
Damstra, A., Lindgren, E., Vliegenthart, R., Boomgaarden, H., Strömbäck, J., & Tsfati, Y. (2025) · Journalism · doi:10.1177/14648849251350374
“This is in line with other studies that also report lower levels of trust when information comes from a social media platform instead of an original news source (e.g., Karlsen and Aalberg, 2023; Newman et al., 2023).”
Johansson, S., & Johansson, B. (2025) · Crisis and Risk Communication · doi:10.1080/29986907.2025.2558684
Tok, İ., & Ulusoy, H. (2025) · Akdeniz Üniversitesi İletişim Fakültesi Dergisi · doi:10.31123/akil.1704664
Reconsidering deepfake priming: effects on belief and sharing across media platforms
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da Silva, G. C. (2022) · theses.fr (ABES) · doi:10.70675/067705c4z4710z45b7za2c2z2c82fd9a0b13 · Cited by 2
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Social Trust, Political Trust and Media Trust
Trenz, H. (2026) · Springer eBooks · doi:10.1007/978-3-032-20797-5_3
Examining the influence of social media cues and platform perceptions on fake news detection
Tang, J., & Millet, B. (2026) · Information Communication & Society · doi:10.1080/1369118x.2026.2667914
Lai, K., & Potočnik, K. (2026) · Journal of Management Studies · doi:10.1111/joms.70109
“@?”: Authorship and Newsroom Image Crediting Practices on Instagram
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Social Expectations of Ukrainian War Migrants (The Case of Poland)
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Zhao, Y., Lin, Z., & Luqiu, L. R. (2026) · Asian Studies Review · doi:10.1080/10357823.2026.2681167
Metadata
- Authors
- Karlsen, R., & Aalberg, T.
- Affiliations
- University of Oslo (NO)
- Norwegian University of Science and Technology (NO)
- Corresponding author
- Karlsen, Rune
- Venue
- Digital Journalism
- Publisher
- Informa UK Limited
- Published
- 2021-07-21
- Volume
- 11
- Issue
- 1
- Pages
- 144-160
- ISSN
- 2167-0811 (ISSN-L)
- 2167-082X
- OpenAlex
- W3189018750
- Cited by
- 119
- References
- 56
- Citations by year
- 2026: 21 · 2025: 32 · 2024: 25 · 2023: 23 · 2022: 16 · 2021: 2
- FWCI
- 22.87
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Digital Journalism (publishedVersion, cc-by-nc-nd)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
- Funders
- Research Council of Norway (249687)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › News Media Framing and Political Communication
- Social Sciences › Communication › Journalism and Media Studies
- Keywords
- social media, Facebook, news credibility, trust in news, news sharing, politicians, political affiliation, fake news, news consumption
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.
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