期刊
BRITISH JOURNAL OF SOCIAL PSYCHOLOGY
卷 61, 期 3, 页码 1011-1031出版社
WILEY
DOI: 10.1111/bjso.12518
关键词
conspiracies; latent variable analysis; monological belief systems; network analysis
资金
- Massey University [RM22245]
A substantial minority of the public express belief in conspiracy theories and those who believe one conspiracy theory are more likely to believe in others. However, the reason behind this positive manifold of belief in conspiracy theories is unclear. This study tested both the unidimensional factor model and a network model, and the results favored the network model, suggesting that beliefs in various conspiracy theories support one another in a mutually reinforcing network of beliefs.
A substantial minority of the public express belief in conspiracy theories. A robust phenomenon in this area is that people who believe one conspiracy theory are more likely to believe in others. But the reason for this positive manifold of belief in conspiracy theories is unclear. One possibility is that a single underlying latent factor (e.g. conspiracism) causes variation in belief in specific conspiracy theories. Another possibility is that beliefs in various conspiracy theories support one another in a mutually reinforcing network of beliefs (the monological belief system theory). While the monological theory has been influential in the literature, the fact that it can be operationalised as a statistical network model has not previously been recognised. In this study, we therefore tested both the unidimensional factor model and a network model. Participants were 1553 American adults recruited via Prolific. Belief in conspiracies was measured using an adapted version of the Belief in Conspiracy Theories Inventory. The fit of the two competing models was evaluated both by using van Bork et al.'s (Psychometrika, 83, 2018, 443, Multivariate Behavioral Research, 56, 2019, 175) method for testing network versus unidimensional factor models, as well as by evaluating goodness of fit to the sample covariance matrix. In both cases, evaluation of fit according to our pre-registered inferential criteria favoured the network model.
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