Analysing networks of networks

被引:3
|
作者
Koskinen, Johan [1 ,2 ]
Jones, Pete [3 ]
Medeuov, Darkhan [4 ]
Antonyuk, Artem [5 ,6 ]
Puzyreva, Kseniia [5 ,6 ]
Basov, Nikita [7 ]
机构
[1] Stockholm Univ, Dept Stat, Stockholm, Sweden
[2] Univ Melbourne, Melbourne Sch Psychol Sci, Social Networks Lab, Melbourne, Australia
[3] Univ Alberta, Fac Arts Interdisciplinary Studies, Edmonton, AB, Canada
[4] Nazarbayev Univ, Astana, Kazakhstan
[5] St Petersburg Univ, Ctr German & European Studies, St Petersburg, Russia
[6] Bielefeld Univ, Bielefeld, Russia
[7] Univ Manchester, Dept Social Stat, Manchester, England
基金
俄罗斯科学基金会;
关键词
Multiplex networks; Multilevel networks; Sociosemantic networks; Multigraphs; ONE-MODE; DYNAMICS; 2-MODE; CONSTRUCTION; INNOVATION; CONSENSUS; CULTURE;
D O I
10.1016/j.socnet.2023.02.002
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
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.
引用
收藏
页码:102 / 117
页数:16
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