Confirmation Bias in the Era of Mobile News Consumption: The Social and Psychological Dimensions
Abstract
Confirmation bias is the predisposition to only consume the news, or what appears to be news, that confirms our pre-existing attitudes and beliefs, e.g. anti-vaxxers reading only anti-vaccination material. This plays out, for example, in reading only the news/postings that fit our political or social leaning. It is done to avoid cognitive dissonance as well as eventual disfavor from our social network. Confirmation bias is an important element supporting the diffusion of false news via digital platforms. It is important that we understand the underlying cognitive as well as the social mechanisms and dynamics, e.g. can the news of COVID-19 disrupt or eventually further entrench the cognitive and social dynamics of anti-vaxxer individuals and groups?
Integrity signals
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Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Social media has become one of the main platforms for public information consumption.
“Social media has become one of the main platforms for public information consumption.”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as Ling, 2020
The ability to share and comment instantly allows information to spread quickly, but also poses challenges regarding the validity and accuracy of the information shared, given the rise of hoax news.
“The ability to share and comment instantly allows information to spread quickly, but also poses challenges regarding the validity and accuracy of the information shared, given the rise of hoax news.(Ling, 2020).”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as Ling, 2020
Sites like Facebook, Twitter, and Instagram serve not only as sources of information but also as tools for sharing news.
“Sites like Facebook, Twitter, and Instagram serve not only as sources of information but also as tools for sharing news.”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as Ling, 2020
This brings a paradigm shift, where people are not only consumers of information but also producers of information.
“This brings a paradigm shift, where people are not only consumers of information but also producers of information.”
From CHANGES IN PUBLIC INFORMATION CONSUMPTION PATTERNS IN THE DIGITAL ERA: A LITERATURE STUDY ON DIGITAL JOURNALISM (2025) · cites this paper as Ling, 2020
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References 42 · Cited by 72
- Authors
- Ling, R.
- Affiliations
- Nanyang Technological University (SG)
- Corresponding author
- Ling, Rich
- ORCID
- Ling, Rich
- Venue
- Digital Journalism
- Publisher
- Informa UK Limited
- Published
- 2020-05-22
- Volume
- 8
- Issue
- 5
- Pages
- 596-604
- ISSN
- 2167-0811 (ISSN-L)
- 2167-082X
- OpenAlex
- W3027050591
- Cited by
- 72
- References
- 42
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 13 · 2023: 19 · 2022: 12 · 2021: 10 · 2020: 1
- FWCI
- 14.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Digital Journalism (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Keywords
- confirmation bias, mobile news consumption, anti-vaxxers, vaccine hesitancy, cognitive dissonance, echo chambers, social networks, political polarization, COVID-19 news, digital platforms
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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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