Extracting deep information from limited observations on an evolved social network

Paul Ormerod ()

Physica A: Statistical Mechanics and its Applications, 2007, vol. 378, issue 1, 48-52

Abstract: We provide empirical evidence that in a social network which evolves over time, it is possible to extract deep information about the system from limited observations. In this paper, we consider a simple piece of readily available evidence on access to financial services by individuals in the UK. Detailed statistical analysis has shown that the decisions of agents on whether or not to have a basic financial account such as a bank account is heavily influenced by other individuals on their social network. We consider a small amount of straightforward and readily accessible information. We deduce from this, using an agent-based model, the type of social network across which information and influence on behaviour flows between agents in this context. Specifically, we show that information appears to flow across a small world network.

Keywords: Empirical social network; Agent-based model; Small world (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:378:y:2007:i:1:p:48-52

DOI: 10.1016/j.physa.2006.11.044

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