Analysing networks of networks
Koskinen J. Jones P. Medeuov D. Antonyuk A. Puzyreva K. Basov N.
July 2023Elsevier B.V.
Social Networks
2023#74102 - 117 pp.
We consider data with multiple observations or reports on a network in the case when these networks themselves are connected through some form of network ties. We could take the example of a cognitive social structure where there is another type of tie connecting the actors that provide the reports; or the study of interpersonal spillover effects from one cultural domain to another facilitated by the social ties. Another example is when the individual semantic structures are represented as semantic networks of a group of actors and connected through these actors’ social ties to constitute knowledge of a social group. How to jointly represent the two types of networks is not trivial as the layers and not the nodes of the layers of the reported networks are coupled through a network on the reports. We propose to transform the different multiple networks using line graphs, where actors are affiliated with ties represented as nodes, and represent the totality of the different types of ties as a multilevel network. This affords studying the associations between the social network and the reports as well as the alignment of the reports to a criterion graph. We illustrate how the procedure can be applied to studying the social construction of knowledge in local flood management groups. Here we use multilevel exponential random graph models but the representation also lends itself to stochastic actor-oriented models, multilevel blockmodels, and any model capable of handling multilevel networks.
Multigraphs , Multilevel networks , Multiplex networks , Sociosemantic networks
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Department of Statistics, Stockholm University, Sweden
The Social Networks Lab, The Melbourne School of Psychological Sciences, University of Melbourne, Australia
Faculty of Arts - Interdisciplinary Studies, University of Alberta, Canada
Nazarbayev University, Kazakhstan
Centre for German and European Studies, St Petersburg University & Bielefeld University, Russian Federation
Department of Social Statistics, University of Manchester, United Kingdom
Department of Statistics
The Social Networks Lab
Faculty of Arts - Interdisciplinary Studies
Nazarbayev University
Centre for German and European Studies
Department of Social Statistics
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