Individuals, Crowds, and the Network Dynamics of Belief Accuracy
Charlie Pilgrim, Joshua Becker

TL;DR
This paper investigates how social influence and network dynamics affect belief accuracy, revealing that individuals tend to improve their accuracy even when group accuracy declines due to factors like herding and influence centralization.
Contribution
It provides a formal model linking individual and group accuracy, clarifies how network effects influence belief formation, and empirically demonstrates individual improvement despite group accuracy decline.
Findings
Individuals improve their accuracy in most conditions.
Group accuracy can decline due to herding and influence centralization.
Change in group error relates to network structure and influence calibration.
Abstract
Does talking to others make people more accurate or less accurate on numeric estimates such as quantitative evaluations or probabilistic forecasts? Research on peer-to-peer communication suggests that discussion between people will usually improve belief accuracy, while research on social networks suggests that error can percolate through groups and reduce accuracy. One challenge to interpreting empirical literature is that some studies measure accuracy at the group level, while others measure individual accuracy. We explain how social influence impacts belief accuracy by analyzing a formal model of opinion formation to identify the relationship between individual accuracy, group accuracy, and the network dynamics of belief formation. When opinions become more similar over time, change in individual error is always strictly better than change in group error, by a value equal to the…
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Taxonomy
TopicsConflict Management and Negotiation
