Deception as a Bridging Concept in the Study of Disinformation, Misinformation, and Misperceptions: Toward a Holistic Framework

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Abstract

We propose deception as a bridging concept that will enhance the study of misinformation, disinformation, and misperceptions. As we set it out here, the concept integrates insights from multiple social science disciplines and uniquely connects actors’ intentions, information, and attitudinal or behavioral outcomes. A focus on deception will enrich research that describes the existence of false and misleading information but stops short of identifying their influence. Equally, through its focus on how actors’ deceptive strategies are important in attempts to exercise power, it can augment the study of the cognitive and attitudinal biases that render people susceptible to misperceptions. We identify the main themes in the study of deception: media-systemic distortions in information supply; the relational interactions that both produce and activate cognitive biases; and the attributes, strategies, and techniques of deceptive entities. We conclude with a summary typology of 10 principal variables and their 57 focal indicators.

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Most cited references 96

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Judgment under Uncertainty: Heuristics and Biases.

A Tversky, D Kahneman (1974)

This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

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Record: found
Abstract: found
Article: not found

The case for motivated reasoning.

Ziva Kunda (1990)

It is proposed that motivation may affect reasoning through reliance on a biased set of cognitive processes--that is, strategies for accessing, constructing, and evaluating beliefs. The motivation to be accurate enhances use of those beliefs and strategies that are considered most appropriate, whereas the motivation to arrive at particular conclusions enhances use of those that are considered most likely to yield the desired conclusion. There is considerable evidence that people are more likely to arrive at conclusions that they want to arrive at, but their ability to do so is constrained by their ability to construct seemingly reasonable justifications for these conclusions. These ideas can account for a wide variety of research concerned with motivated reasoning.