Inferring personal economic status from social network location. Luo, S., Morone, F., Sarraute, C., Travizano, M., & Makse, H. A. Nature Communications, May, 2017. ![Inferring personal economic status from social network location [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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., It is believed that patterns of social ties are related to individuals' financial status. Here the authors substantiate this concept by quantitatively demonstrating that a measure of an individual's location and influence within their social network can be used to infer their economic wellness.
@article{luo_inferring_2017,
title = {Inferring personal economic status from social network location},
volume = {8},
issn = {2041-1723},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440802/},
doi = {10.1038/ncomms15227},
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., It is believed that patterns of social ties are related to individuals' financial status. Here the authors substantiate this concept by quantitatively demonstrating that a measure of an individual's location and influence within their social network can be used to infer their economic wellness.},
urldate = {2017-10-30},
journal = {Nature Communications},
author = {Luo, Shaojun and Morone, Flaviano and Sarraute, Carlos and Travizano, Matías and Makse, Hernán A.},
month = may,
year = {2017},
pmid = {28509896},
pmcid = {PMC5440802},
keywords = {🌟高质量期刊},
}
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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., It is believed that patterns of social ties are related to individuals' financial status. 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