Communication dynamics in finite capacity social networks

Jan Olaf Mirko Härter; Bjørn Jamtveit; Joachim Mathiesen

doi:10.1103/PhysRevLett.109.168701

Communication dynamics in finite capacity social networks

Jan Olaf Mirko Härter, Bjørn Jamtveit, Joachim Mathiesen

Biokompleksitet

31 Citationer (Scopus)

Abstract

In communication networks, structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and dynamics, a generic model, based on the local interaction between nodes, is considered for the communication in large social networks. In agreement with data from a large human organization, we show that the flow is non-Markovian and controlled by the temporal limitations of individuals. We confirm the versatility of our model by predicting simultaneously the degree-dependent node activity, the balance between information input and output of nodes, and the degree distribution. Finally, we quantify the limitations to network analysis when it is based on data sampled over a finite period of time.

Originalsprog	Engelsk
Tidsskrift	Physical Review Letters
Vol/bind	109
Udgave nummer	16
Sider (fra-til)	168701
Antal sider	5
ISSN	0031-9007
DOI	https://doi.org/10.1103/PhysRevLett.109.168701
Status	Udgivet - 15 okt. 2012

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10.1103/PhysRevLett.109.168701

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AU - Härter, Jan Olaf Mirko

AU - Jamtveit, Bjørn

AU - Mathiesen, Joachim

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AB - In communication networks, structure and dynamics are tightly coupled. The structure controls the flow of information and is itself shaped by the dynamical process of information exchanged between nodes. In order to reconcile structure and dynamics, a generic model, based on the local interaction between nodes, is considered for the communication in large social networks. In agreement with data from a large human organization, we show that the flow is non-Markovian and controlled by the temporal limitations of individuals. We confirm the versatility of our model by predicting simultaneously the degree-dependent node activity, the balance between information input and output of nodes, and the degree distribution. Finally, we quantify the limitations to network analysis when it is based on data sampled over a finite period of time.

U2 - 10.1103/PhysRevLett.109.168701

DO - 10.1103/PhysRevLett.109.168701

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JF - Physical Review Letters

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Communication dynamics in finite capacity social networks

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