The empirical study of network dynamics has been limited by the lack of
longitudinal data. Here we introduce a quantitative indicator of link
persistence to explore the correlations between the structure of a mobile phone
network and the persistence of its links. We show that persistent links tend to
be reciprocal and are more common for people with low degree and high
clustering. We study the redundancy of the associations between persistence,
degree, clustering and reciprocity and show that reciprocity is the strongest
predictor of tie persistence. The method presented can be easily adapted to
characterize the dynamics of other networks and can be used to identify the
links that are most likely to survive in the future.
%0 Journal Article
%1 Hidalgo2008Dynamics
%A Hidalgo, Cesar A.
%A Rodriguez-Sickert, C.
%D 2008
%J Physica A: Statistical Mechanics and its Applications
%K networks temporal-networks mobile-phones human-mobility
%N 12
%P 3017--3024
%R 10.1016/j.physa.2008.01.073
%T The Dynamics of a Mobile Phone Network
%U http://dx.doi.org/10.1016/j.physa.2008.01.073
%V 387
%X The empirical study of network dynamics has been limited by the lack of
longitudinal data. Here we introduce a quantitative indicator of link
persistence to explore the correlations between the structure of a mobile phone
network and the persistence of its links. We show that persistent links tend to
be reciprocal and are more common for people with low degree and high
clustering. We study the redundancy of the associations between persistence,
degree, clustering and reciprocity and show that reciprocity is the strongest
predictor of tie persistence. The method presented can be easily adapted to
characterize the dynamics of other networks and can be used to identify the
links that are most likely to survive in the future.
@article{Hidalgo2008Dynamics,
abstract = {{The empirical study of network dynamics has been limited by the lack of
longitudinal data. Here we introduce a quantitative indicator of link
persistence to explore the correlations between the structure of a mobile phone
network and the persistence of its links. We show that persistent links tend to
be reciprocal and are more common for people with low degree and high
clustering. We study the redundancy of the associations between persistence,
degree, clustering and reciprocity and show that reciprocity is the strongest
predictor of tie persistence. The method presented can be easily adapted to
characterize the dynamics of other networks and can be used to identify the
links that are most likely to survive in the future.}},
added-at = {2019-06-10T14:53:09.000+0200},
archiveprefix = {arXiv},
author = {Hidalgo, Cesar A. and Rodriguez-Sickert, C.},
biburl = {https://www.bibsonomy.org/bibtex/2586ddf2a612fd740927a764084c149f1/nonancourt},
citeulike-article-id = {3129718},
citeulike-linkout-0 = {http://arxiv.org/abs/0712.4031},
citeulike-linkout-1 = {http://arxiv.org/pdf/0712.4031},
citeulike-linkout-2 = {http://dx.doi.org/10.1016/j.physa.2008.01.073},
citeulike-linkout-3 = {http://www.sciencedirect.com/science/article/B6TVG-4RM7MXN-5/2/3f55af67920a2a2763b8944d88c760d0},
day = 11,
doi = {10.1016/j.physa.2008.01.073},
eprint = {0712.4031},
interhash = {a5ea773bac60ff2f68746e92d906e71f},
intrahash = {586ddf2a612fd740927a764084c149f1},
issn = {03784371},
journal = {Physica A: Statistical Mechanics and its Applications},
keywords = {networks temporal-networks mobile-phones human-mobility},
month = may,
number = 12,
pages = {3017--3024},
posted-at = {2009-07-10 10:44:24},
priority = {2},
timestamp = {2019-08-01T16:16:14.000+0200},
title = {{The Dynamics of a Mobile Phone Network}},
url = {http://dx.doi.org/10.1016/j.physa.2008.01.073},
volume = 387,
year = 2008
}