To illuminate and motivate: a fuzzy-trace model of the spread of information online

David A. Broniatowski () and Valerie F. Reyna
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David A. Broniatowski: The George Washington University
Valerie F. Reyna: Cornell University

Computational and Mathematical Organization Theory, 2020, vol. 26, issue 4, No 4, 464 pages

Abstract: Abstract We propose, and test, a model of online media platform users’ decisions to act on, and share, received information. Specifically, we focus on how mental representations of message content drive its spread. Our model is based on fuzzy-trace theory (FTT), a leading theory of decision under risk. Per FTT, online content is mentally represented in two ways: verbatim (objective, but decontextualized, facts), and gist (subjective, but meaningful, interpretation). Although encoded in parallel, gist tends to drive behaviors more strongly than verbatim representations for most individuals. Our model uses factors derived from FTT to make predictions regarding which content is more likely to be shared, namely: (a) different levels of mental representation, (b) the motivational content of a message, (c) difficulty of information processing (e.g., the ease with which a given message may be comprehended and, therefore, its gist extracted), and (d) social values.

Keywords: Gist; Verbatim; Vaccines; Misinformation; twitter (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10588-019-09297-2

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