TY - JOUR
T1 - Multiscale mixing patterns in networks
AU - Peel, Leto
AU - Delvenne, Jean Charles
AU - Lambiotte, Renaud
N1 - Funding Information:
ACKNOWLEDGMENTS. This work was supported by Concerted Research Action (ARC) supported by the Federation Wallonia-Brussels Contract ARC 14/19-060 (to L.P., J.-C.D., and R.L.); Fonds de la Recherche Scientifique-Fonds National de le Recherche Scientifique (L.P.); and Flagship European Research Area Network (FLAG-ERA) Joint Transnational Call “FuturICT 2.0” (J.-C.D. and R.L.).
Funding Information:
This work was supported by Concerted Research Action (ARC) supported by the Federation Wallonia-Brussels Contract ARC 14/19-060 (to L.P., J.-C.D., and R.L.); Fonds de la Recherche Scientifique-Fonds National de le Recherche Scientifique (L.P.); and Flagship European Research Area Network (FLAG-ERA) Joint Transnational Call “FuturICT 2.0” (J.-C.D. and R.L.).
Publisher Copyright:
© 2018 National Academy of Sciences. All rights reserved.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/4/17
Y1 - 2018/4/17
N2 - Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks, manifesting as a higher tendency of links occurring between people of the same age, race, or political belief. Quantifying the level of assortativity or disassortativity (the preference of linking to nodes with different attributes) can shed light on the organization of complex networks. It is common practice to measure the level of assortativity according to the assortativity coefficient, or modularity in the case of categorical metadata. This global value is the average level of assortativity across the network and may not be a representative statistic when mixing patterns are heterogeneous. For example, a social network spanning the globe may exhibit local differences in mixing patterns as a consequence of differences in cultural norms. Here, we introduce an approach to localize this global measure so that we can describe the assortativity, across multiple scales, at the node level. Consequently, we are able to capture and qualitatively evaluate the distribution of mixing patterns in the network. We find that, for many real-world networks, the distribution of assortativity is skewed, overdispersed, and multimodal. Our method provides a clearer lens through which we can more closely examine mixing patterns in networks.
AB - Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks, manifesting as a higher tendency of links occurring between people of the same age, race, or political belief. Quantifying the level of assortativity or disassortativity (the preference of linking to nodes with different attributes) can shed light on the organization of complex networks. It is common practice to measure the level of assortativity according to the assortativity coefficient, or modularity in the case of categorical metadata. This global value is the average level of assortativity across the network and may not be a representative statistic when mixing patterns are heterogeneous. For example, a social network spanning the globe may exhibit local differences in mixing patterns as a consequence of differences in cultural norms. Here, we introduce an approach to localize this global measure so that we can describe the assortativity, across multiple scales, at the node level. Consequently, we are able to capture and qualitatively evaluate the distribution of mixing patterns in the network. We find that, for many real-world networks, the distribution of assortativity is skewed, overdispersed, and multimodal. Our method provides a clearer lens through which we can more closely examine mixing patterns in networks.
KW - Assortativity
KW - Complex networks
KW - Multiscale
KW - Node metadata
UR - http://www.scopus.com/inward/record.url?scp=85045633568&partnerID=8YFLogxK
UR - http://arxiv.org/abs/1708.01236
http://dx.doi.org/10.1073/pnas.1713019115
UR - http://www.mendeley.com/research/multiscale-mixing-patterns-networks
U2 - 10.1073/pnas.1713019115
DO - 10.1073/pnas.1713019115
M3 - Article
AN - SCOPUS:85045633568
SN - 0027-8424
VL - 115
SP - 4057
EP - 4062
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 16
ER -