dorsal/arxiv
View SchemaA mean-field analysis of community structure in social and kin networks
| Authors | E. Durand, M. G. B Blum, O. Francois |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0604016 |
| URL | https://arxiv.org/abs/q-bio/0604016 |
Abstract
We provide a mean-field analysis of community structure of social and biological networks assuming that actors are able to evaluate some tree-derived distance to the other actors and tend to aggregate with the less distant. We show that such networks have small components, and give exact descriptions for the probability distribution of a typical community size and the number of communities. In particular, we show that the probability distribution of the community size is well-approximated by a power-law distribution with exponent two. We illustrate the robustness of the mean-field analysis by comparing its predictions on previously studied social networks and biological data.
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"abstract": "We provide a mean-field analysis of community structure of social and\nbiological networks assuming that actors are able to evaluate some tree-derived\ndistance to the other actors and tend to aggregate with the less distant. We\nshow that such networks have small components, and give exact descriptions for\nthe probability distribution of a typical community size and the number of\ncommunities. In particular, we show that the probability distribution of the\ncommunity size is well-approximated by a power-law distribution with exponent\ntwo. We illustrate the robustness of the mean-field analysis by comparing its\npredictions on previously studied social networks and biological data.",
"arxiv_id": "q-bio/0604016",
"authors": [
"E. Durand",
"M. G. B Blum",
"O. Francois"
],
"categories": [
"q-bio.PE",
"math.PR",
"physics.soc-ph"
],
"title": "A mean-field analysis of community structure in social and kin networks",
"url": "https://arxiv.org/abs/q-bio/0604016"
},
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