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Identifying and modeling the structural discontinuities of human interactions
Sebastian Grauwin1, Michael Szell1,2,3, Stanislav Sobolevsky1,4
1Senseable City Lab, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Scientific Reports
|April 27, 2017
Summary
Borders significantly reduce communication between regions, a factor missing in current human interaction models. Incorporating this border effect improves predictions for social activities and infrastructure planning.
Area of Science:
- Human Geography
- Network Science
- Computational Social Science
Background:
- Societal organization theories emphasize hierarchical spatial structures.
- Large-scale mobility and communication data reveal geographical confinement of human interactions.
- Existing interaction models often overlook the impact of borders on communication.
Purpose of the Study:
- To identify and quantify the impact of national borders on human communication patterns.
- To develop an improved modeling framework that accounts for border effects.
- To enhance the predictive accuracy of human interaction models.
Main Methods:
- Analysis of country-wide telephone call networks (mobile and landline).
- Statistical modeling to identify border-induced communication damping.
- Integration of border effects into existing interaction models.
Main Results:
- A systematic decrease in communication across national borders was observed.
- Borders were identified as a critical missing variable in current models.
- The proposed model incorporating border effects significantly improved predictive power.
Conclusions:
- National borders exert a measurable damping effect on human communication.
- Accounting for border effects is crucial for accurately modeling social interactions.
- Improved models enhance understanding and prediction of social activities and infrastructure needs.
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