The limits of epidemiological models of misinformation

Abstract Empirical social sciences routinely model misinformation as exhibiting dynamics analogous to vaccinable diseases or contagious outbreaks, as in inoculation theory and other epidemiological models. However, idiosyncratic features of the social construction of misinformation violate the biological analogy in significant ways, rendering these models far weaker in effect size, predictive accuracy, and explanatory power than has been claimed. Four arguments are discussed regarding problems with the ontology of misinformation posited in these models, methods for measuring misinformation, individuation of mechanisms, and application of interventions. A conclusion is drawn that model transfer from biology has often been unwarranted in misinformation studies and that alternative methods should be pursued instead.

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Publication Details

Journal
Synthese
Published
2025-09-10
DOI
https://doi.org/10.1007/s11229-025-05246-6
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
4.20

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article

The limits of epidemiological models of misinformation

Adrian K. Yee
1 citations
Synthese
Misinformation and Its Impacts
4.20
article

The limits of epidemiological models of misinformation

Adrian K. Yee
article en
1 citations

Abstract

Abstract Empirical social sciences routinely model misinformation as exhibiting dynamics analogous to vaccinable diseases or contagious outbreaks, as in inoculation theory and other epidemiological models. However, idiosyncratic features of the social construction of misinformation violate the biological analogy in significant ways, rendering these models far weaker in effect size, predictive accuracy, and explanatory power than has been claimed. Four arguments are discussed regarding problems with the ontology of misinformation posited in these models, methods for measuring misinformation, individuation of mechanisms, and application of interventions. A conclusion is drawn that model transfer from biology has often been unwarranted in misinformation studies and that alternative methods should be pursued instead.

SyntheseVol. 206(3)
Lingnan University (HK)
Lingnan University, Hong Kong Government
Openalex Percentile: Top 6%
Misinformation and Its Impacts
4.20
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