TY - JOUR
T1 - Delineating geographical regions with networks of human interactions in an extensive set of countries
AU - Sobolevsky, Stanislav
AU - Szell, Michael
AU - Campari, Riccardo
AU - Couronné, Thomas
AU - Smoreda, Zbigniew
AU - Ratti, Carlo
PY - 2013
Y1 - 2013
N2 - Large-scale networks of human interaction, in particular country-wide telephone call networks, can be used to redraw geographical maps by applying algorithms of topological community detection. The geographic projections of the emerging areas in a few recent studies on single regions have been suggested to share two distinct properties: first, they are cohesive, and second, they tend to closely follow socio-economic boundaries and are similar to existing political regions in size and number. Here we use an extended set of countries and clustering indices to quantify overlaps, providing ample additional evidence for these observations using phone data from countries of various scales across Europe, Asia, and Africa: France, the UK, Italy, Belgium, Portugal, Saudi Arabia, and Ivory Coast. In our analysis we use the known approach of partitioning country-wide networks, and an additional iterative partitioning of each of the first level communities into sub-communities, revealing that cohesiveness and matching of official regions can also be observed on a second level if spatial resolution of the data is high enough. The method has possible policy implications on the definition of the borderlines and sizes of administrative regions.
AB - Large-scale networks of human interaction, in particular country-wide telephone call networks, can be used to redraw geographical maps by applying algorithms of topological community detection. The geographic projections of the emerging areas in a few recent studies on single regions have been suggested to share two distinct properties: first, they are cohesive, and second, they tend to closely follow socio-economic boundaries and are similar to existing political regions in size and number. Here we use an extended set of countries and clustering indices to quantify overlaps, providing ample additional evidence for these observations using phone data from countries of various scales across Europe, Asia, and Africa: France, the UK, Italy, Belgium, Portugal, Saudi Arabia, and Ivory Coast. In our analysis we use the known approach of partitioning country-wide networks, and an additional iterative partitioning of each of the first level communities into sub-communities, revealing that cohesiveness and matching of official regions can also be observed on a second level if spatial resolution of the data is high enough. The method has possible policy implications on the definition of the borderlines and sizes of administrative regions.
KW - Topological Community Detection
KW - Geographical Maps
KW - Socio-Economic Boundaries
KW - Telephone Call Networks
KW - Administrative Regions
KW - Topological Community Detection
KW - Geographical Maps
KW - Socio-Economic Boundaries
KW - Telephone Call Networks
KW - Administrative Regions
U2 - 10.1371/journal.pone.0081707
DO - 10.1371/journal.pone.0081707
M3 - Tidsskriftartikel
SN - 1932-6203
VL - 8
SP - e81707
JO - PLOS ONE
JF - PLOS ONE
IS - 12
ER -