Information flows and crashes in dynamic social networks

Phillip J. Monin () and Richard Bookstaber ()
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Phillip J. Monin: Federal Reserve Board of Governors
Richard Bookstaber: University of California

Journal of Economic Interaction and Coordination, 2021, vol. 16, issue 3, No 2, 495 pages

Abstract: Abstract We develop a dynamic model of information transmission and aggregation in social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity, in which agents’ opinions are widely dispersed.

Keywords: Social networks; DeGroot learning; Dynamic network formation; Information transmission; Agent-based model; Crashes (search for similar items in EconPapers)
JEL-codes: D83 D85 Z13 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11403-020-00310-5

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