Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.
Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap...
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doaj-405c4765181b4ae2949c0ffbbb1633fa2020-11-24T21:27:11ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01105e012671310.1371/journal.pone.0126713Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.Zsófia KallusNorbert BarankaiJános SzüleGábor VattayHuman interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.http://europepmc.org/articles/PMC4439170?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zsófia Kallus Norbert Barankai János Szüle Gábor Vattay |
spellingShingle |
Zsófia Kallus Norbert Barankai János Szüle Gábor Vattay Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. PLoS ONE |
author_facet |
Zsófia Kallus Norbert Barankai János Szüle Gábor Vattay |
author_sort |
Zsófia Kallus |
title |
Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
title_short |
Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
title_full |
Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
title_fullStr |
Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
title_full_unstemmed |
Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
title_sort |
spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2015-01-01 |
description |
Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. |
url |
http://europepmc.org/articles/PMC4439170?pdf=render |
work_keys_str_mv |
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