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

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

Proskurnikov, A.V. (TU Delft Team Tamas Keviczky; ITMO University; Russian Academy of Sciences)
Tempo, Roberto (Politecnico di Torino; National Research Council)

2017

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.

Distributed algorithms
Multi-agent systems
Opinion dynamics
Social network

http://resolver.tudelft.nl/uuid:d6a5207e-4828-414f-8917-38cb4cf035f5

https://doi.org/10.1016/j.arcontrol.2017.03.002

2019-05-12

1367-5788

Annual Reviews in Control, 43, 65-79

Accepted Author Manuscript Corrigendum to ‘‘A tutorial on modeling and analysis of dynamic social networks. Part I.’’ [Annu. Rev. Control 43 (2017) 65–79]: https://doi.org/10.1016/j.arcontrol.2020.12.003

Institutional Repository

review

© 2017 A.V. Proskurnikov, Roberto Tempo