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Bootstrap methods for the empirical study of decision-making and information flows in social systems
journal contribution
posted on 2023-06-08, 16:37 authored by Simon DeDeo, Robert Hawkins, Sara Klingenstein, Tim HitchcockAbstract: We characterize the statistical bootstrap for the estimation of information theoretic quantities from data, with particular reference to its use in the study of large-scale social phenomena. Our methods allow one to preserve, approximately, the underlying axiomatic relationships of information theory—in particular, consistency under arbitrary coarse-graining—that motivate use of these quantities in the first place, while providing reliability comparable to the state of the art for Bayesian estimators. We show how information-theoretic quantities allow for rigorous empirical study of the decision-making capacities of rational agents, and the time-asymmetric flows of information in distributed systems. We provide illustrative examples by reference to ongoing collaborative work on the semantic structure of the British Criminal Court system and the conflict dynamics of the contemporary Afghanistan insurgency.
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- Published
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- Published version
Journal
EntropyISSN
1099-4300Publisher
MDPI AGExternal DOI
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6Volume
15Page range
2246-2276Department affiliated with
- History Publications
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- Yes
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- Yes
Legacy Posted Date
2014-07-02First Open Access (FOA) Date
2014-07-02First Compliant Deposit (FCD) Date
2014-01-15Usage metrics
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