Abstract
When a set of people interact frequently with one another, they often grow to think more and more along the same lines, a phenomenon we call "collective cognitive convergence" (C3). We discuss instances of C3 and why it is advantageous or disadvantageous; review previous work in sociology, computational social science, and evolutionary biology that sheds light on C3; define a computational model for the convergence process and quantitative metrics that can be used to study it; report on experiments with this model and metric; and suggest how the insights from this model can inspire techniques for managing C3.
Cite
CITATION STYLE
Parunak, H. V., Belding, T. C., Hilscher, R., & Brueckner, S. (2009). Understanding collective cognitive convergence. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5269, pp. 127–140). https://doi.org/10.1007/978-3-642-01991-3_10
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