He did it! She did it! No, she did not! Multiple causal explanations and the continued influence of misinformation

By Ullrich K. H. Ecker, Stephan Lewandowsky, C. S. Cheung, Murray Maybery. 2015

97 citations recorded by the source corpus.

Two types of misinformation effects are discussed in the literature—the post-event misinformation effect and the continued influence effect. The former refers to the distorting memorial effects of misleading information that is presented after valid event encoding; the latter refers to information that is initially presented as true but subsequently turns out to be false and continues to affect memory and reasoning despite the correction. In two experiments, using a paradigm that merges elements from both traditions, we investigated the role of presentation order and recency when two competing causal explanations for an event are presented and one is subsequently retracted. Theoretical accounts of misinformation effects make diverging predictions regarding the roles of presentation order and recency. A recency account—derived from time-based models of memory and reading comprehension research suggesting efficient situation model updating—predicts that the more recently presented cause should have a stronger influence on memory and reasoning. By contrast, a primacy account—derived from primacy effects in impression formation and story recall as well as findings of inadequate memory updating—predicts that the initially presented cause should be dominant irrespective of temporal factors. Results indicated that (1) a cause’s recency, rather than its position (i.e., whether it was presented first or last) determined the emphasis that people place on it in their later reasoning, with more recent explanations being preferred; and (2) a retraction was equally effective whether it invalidated the first or the second cause, as long as the cause’s recency was held constant. This provides evidence against the primacy account and supports time-based models of memory such as temporal distinctiveness theory.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/4360808d50f44a0f39ef06666e25f1e81ca03b47

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Citations in the corpus

Countering Misinformation and Fake News Through Inoculation and Prebunking (2021, background): “Telling people instead that arson, rather than negligence, was to blame for the fire (by referring to petrol-soaked rags that were found at the scene), successfully eliminates reliance on the initial misinformation (e.g., Ecker et al., 2015, 2010; Johnson & Seifert, 1994).”
Educative Interventions to Combat Misinformation: Evidence from a Field Experiment in India (2020, background): “Additionally, strong social connections between fact checkers and rumor spreaders can encourage the latter to be more accepting of corrections (Margolin, Hannak, and Weber 2018), and interventions that come early before a false narrative gains traction can be more effective (Ecker et al. 2015).”
Political Attitudes and the Processing of Misinformation Corrections (2018, background): “The main dependent variable was the mean number of references to the critical information participants made in response to the questionnaire (following ample precedent, e.g., Ecker et al., 2015, 2017; Johnson & Seifert, 1994).”