Inferring personal economic status from social network location

Nature Communications
Shaojun LuoHernán A Makse

Abstract

It is commonly believed that patterns of social ties affect individuals' economic status. Here we translate this concept into an operational definition at the network level, which allows us to infer the economic well-being of individuals through a measure of their location and influence in the social network. We analyse two large-scale sources: telecommunications and financial data of a whole country's population. Our results show that an individual's location, measured as the optimal collective influence to the structural integrity of the social network, is highly correlated with personal economic status. The observed social network patterns of influence mimic the patterns of economic inequality. For pragmatic use and validation, we carry out a marketing campaign that shows a threefold increase in response rate by targeting individuals identified by our social network metrics as compared to random targeting. Our strategy can also be useful in maximizing the effects of large-scale economic stimulus policies.

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Citations

Aug 11, 2020·Journal of Complex Networks·Sen PeiHernán A Makse
Oct 29, 2020·Journal of the Royal Society, Interface·Till Hoffmann, Nick S Jones
Apr 13, 2021·Expert Opinion on Drug Discovery·Finlay MacLean
Jul 3, 2021·Entropy·Jacob Levy Abitbol, Alfredo J Morales
Aug 14, 2021·Research : a Science Partner Journal·Yafei ZhangAlex 'Sandy' Pentland

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