This is a recurring event: View all events in the series “Computational Political Psychology Network Autumn Meetings ”
This event is part of the Autumn Meetings organized by the Computational Political Psychology Network.
Abstract
The same persuasive message can be interpreted in a positive or negative way, challenging our ability to predict its effectiveness. Causal reasoning can contribute to this process of interpretation and produce attitude reversals due to the network structure of beliefs.
I will present the results of two vignette experiments, one based on the famous slogan of the car rental agency Avis (“We're No. 2—that means we try harder”), and the other based on online product reviews.
When participants’ contextual beliefs about the economic environment are manipulated, message effectiveness changes as predicted by a Bayesian mechanism in which seemingly negative information is “explained away” in a more positive light, or vice versa. Thus, causal reasoning may help account for certain counterintuitive kinds of high-level attitude change.
Speaker
Rahul Bihi, Massachusetts Institute of Technology
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