A tutorial on modeling and analysis of dynamic social networks. Part I

Review (2017)
Author(s)

A. V. Proskurnikov (TU Delft - Team Tamas Keviczky, Russian Academy of Sciences, ITMO University)

Roberto Tempo (National Research Council, Politecnico di Torino)

Research Group
Team Tamas Keviczky
Copyright
© 2017 A.V. Proskurnikov, Roberto Tempo
DOI related publication
https://doi.org/10.1016/j.arcontrol.2017.03.002
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 A.V. Proskurnikov, Roberto Tempo
Research Group
Team Tamas Keviczky
Volume number
43
Pages (from-to)
65-79
Reuse Rights

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Abstract

In recent years, we have observed a significant trend towards filling the gap between social network analysis and control. This trend was enabled by the introduction of new mathematical models describing dynamics of social groups, the advancement in complex networks theory and multi-agent systems, and the development of modern computational tools for big data analysis. The aim of this tutorial is to highlight a novel chapter of control theory, dealing with applications to social systems, to the attention of the broad research community. This paper is the first part of the tutorial, and it is focused on the most classical models of social dynamics and on their relations to the recent achievements in multi-agent systems.

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