Abstract
A social network is not only a system of connections or relationships, but pathways along which ideas from various communities may flow. Here we show that the economic development of U.S. states may be predicted by using quantitative measures of their social tie network structure derived from location-based social media. We find that long ties, defined here as ties between people in different states, are strongly correlated with economic development in the US states from 2009–2012 in terms of GDP, patents, and number of startups. In contrast, within-state ties are much less predictive of economic development. Our results suggest that such long ties support innovation by enabling more effective idea flow.
Research was partially sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053 (the ARL Network Science CTA) and by the Office of Naval Research Contract N00014-15-1-2640. The content of this paper does not necessarily reflect the position or policy of the U.S. Government, ARL or ONR, no official endorsement should be inferred or implied.
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Holzbauer, B.O., Szymanski, B.K., Nguyen, T., Pentland, A. (2016). Social Ties as Predictors of Economic Development. In: Wierzbicki, A., Brandes, U., Schweitzer, F., Pedreschi, D. (eds) Advances in Network Science. NetSci-X 2016. Lecture Notes in Computer Science(), vol 9564. Springer, Cham. https://doi.org/10.1007/978-3-319-28361-6_15
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DOI: https://doi.org/10.1007/978-3-319-28361-6_15
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