Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization

Shane T. Mueller () and Yin-Yin Sarah Tan ()
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Shane T. Mueller: Michigan Technological University
Yin-Yin Sarah Tan: Michigan Technological University

Journal of Computational Social Science, 2018, vol. 1, issue 1, No 3, 15-48

Abstract: Abstract Two phenomena that are central to simulation research on opinion dynamics are opinion divergence—the result that individuals interacting in a group do not always collapse to a single viewpoint, and group polarization—the result that average group opinions can become more extreme after discussions than they were to begin with. Standard approaches to modeling these dynamics have typically assumed that agents have an influence bound, such that individuals ignore opinions that differ from theirs by more than some threshold, and thus converge to distinct groups that remain uninfluenced by other distinct beliefs. Additionally, models have attempted to account for group polarization either by assuming the existence of recalcitrant extremists, who draw others to their view without being influenced by them, or negative reaction—movement in opinion space away from those they disagree with. Yet these assumptions are not well supported by existing social/cognitive theory and data, and insofar as there are data, it is often mixed. Moreover, an alternative cognitive assumption is able to produce both of these phenomena: the need for consistency within a set of related beliefs. Via simulation, we show that assumptions about knowledge or belief spaces and conceptual coherence naturally produce both convergence to distinct groups and group polarization, providing an alternative cognitively grounded mechanism for these phenomena.

Keywords: Group polarization; Opinion dynamics; Consensus formation (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s42001-017-0004-7

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