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Literature review | Open Access

Evolutionary information dynamics over social networks: a review

Hangjing Zhang1( ), Yan Chen1, H. Vicky Zhao2
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
Department of Automation, Tsinghua University, Beijing, China
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Abstract

Purpose

The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control.

Design/methodology/approach

It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem.

Findings

By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states.

Originality/value

In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.

Keywords

Crowd behaviour analysisInformation diffusionEvolutionary game theory

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International Journal of Crowd Science
Volume 4 Issue 1,
March 2020
Pages 45-59
DOI: 10.1108/IJCS-09-2019-0026
Cite this article:
Zhang H, Chen Y, Zhao HV. Evolutionary information dynamics over social networks: a review. International Journal of Crowd Science, 2020, 4(1): 45-59. https://doi.org/10.1108/IJCS-09-2019-0026

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Received: 30 September 2019
Revised: 29 November 2019
Accepted: 02 December 2019
Published: 03 February 2020
© The author(s)

Hangjing Zhang, Yan Chen and H. Vicky Zhao. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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