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The Impact of Affect on the Perception of Fake News on Social Media: A Systematic Review
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Social media platforms, which are ripe with emotionally charged pieces of information, are vulnerable to the dissemination of vast amounts of misinformation. Little is known about the affective processing that underlies peoples’ belief in and dissemination of fake news on social media, with the research on fake news predominantly focusing on cognitive processing aspects. This study presents a systematic review of the impact of affective constructs on the perception of fake news on social media platforms. A comprehensive literature search was conducted in the SCOPUS and Web of Science databases to identify relevant articles on the topics of affect, misinformation, disinformation, and fake news. A total of 31 empirical articles were obtained and analyzed. Seven research themes and four research gaps emerged from this review. The findings of this review complement the existing literature on the cognitive mechanisms behind how people perceive fake news on social media. This can have implications for technology platforms, governments, and citizens interested in combating infodemics.
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“Growing scientific evidence shows that negative emotions, such as fear, anger, anxiety, and sadness, are systematically used on social media to amplify the spread of disinformation and, importantly, online engagement -to the benefit of social media platforms (Ali Adeeb & Mirhoseini, 2023).”
From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as Ali Adeeb & Mirhoseini, 2023
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Metadata
- Authors
- Ali Adeeb, R., & Mirhoseini, M.
- Affiliations
- Department of Supply Chain and Business Technology Management, John Molson School of Business, 1450 Guy St, Montreal, QC H3H 0A1, Canada
- Venue
- Social Sciences
- Publisher
- MDPI AG
- Published
- 2023-12-06
- Volume
- 12
- Issue
- 12
- Pages
- 674
- ISSN
- 2076-0760 (ISSN-L)
- OpenAlex
- W4389387138
- Cited by
- 45
- References
- 113
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 7 · 2023: 1
- FWCI
- 1.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Social Sciences (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Fonds de recherche du Québec – Société et culture (FRQSC) (2023-NP-312527)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- fake news, misinformation, disinformation, affect, emotions, social media, infodemic, emotional processing
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.
What counts as a claim ›How we measure confidence ›How we check this ›
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