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Evolution through bursts: Network structure develops through localized bursts in time and space

Published online by Cambridge University Press:  31 August 2016

HILLA BROT
Affiliation:
Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA Kellogg School of Management, Northwestern University, Evanston, IL 60208, USA (e-mail: [email protected])
LEV MUCHNIK
Affiliation:
School of Business Administration, The Hebrew University of Jerusalem, Jerusalem 91905, Israel (e-mail: [email protected])
JACOB GOLDENBERG
Affiliation:
School of Business Administration, IDC Herzliya, Herzliya 46150, Israel (e-mail: [email protected])
YORAM LOUZOUN
Affiliation:
Department of Mathematics, Bar-Ilan University, Ramat Gan 52900, Israel Gonda Brain Research Center, Bar-Ilan University, Ramat Gan 52900, Israel (e-mail: [email protected])

Abstract

Models of network evolution are based on the implicit assumption that network growth is continuous, uniform, and steady. Using the data collected from a large online-blogging platform, we show that the addition and removal of network ties by users do not occur sporadically at isolated nodes spread all over the network, as assumed by the vast majority of stochastic network models, but rather occur in brief bursts of intense local activity.

These bursts of network growth and attrition (addition and removal of network ties) are highly localized around focal nodes. Such network changes coincide with nearly instantaneous densification of the ties between the affected nodes, resulting in an increase of local clustering. Furthermore, we find that these network changes are tightly coupled to the dynamics of individual attributes, particularly the increase in homology between neighboring nodes (homophily) within the scope of the burst. Coincidence of the localized network change with the increase in homophily suggests a strong coupling between the selection and influence processes that lead to simultaneous elevation of assortativity and clustering.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2016 

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