scholarly journals Evolutionary information dynamics over social networks: a review

2020 ◽  
Vol 4 (1) ◽  
pp. 45-59
Author(s):  
Hangjing Zhang ◽  
Yan Chen ◽  
H. Vicky Zhao
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Evolutionary Game ◽  
Evolutionary Information ◽  
Stable States ◽  
Information Dynamics ◽  
Content Type ◽  
Rumor Control

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.

scholarly journals A review on graphical evolutionary game for information diffusion on social networks

2018 ◽  
Vol 2 (3) ◽  
pp. 259-271
Author(s):  
Benliu Qiu ◽  
Ningxuan Zhang
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Design Methodology ◽  
Evolutionary Game ◽  
Biological Evolution ◽  
Technology Research ◽  
Static State ◽  
Content Type

Purpose With the recent development of science and technology, research on information diffusion has become increasingly important. Design/methodology/approach To analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution. Findings Through this method, one can study and even predict information diffusion. Originality/value This paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 317-331
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of pl ion propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

scholarly journals A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Mode Choice ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Game Model ◽  
Stable States ◽  
Taxi Service ◽  
Service Mode ◽  
The Impact

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.

Trust strategy simulation of corporation–NPO cross alliance using evolutionary game theory

Kybernetes ◽  
2017 ◽  
Vol 46 (3) ◽  
pp. 450-465 ◽  
Author(s):  
Yidan Chen ◽  
Lanying Sun
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nonprofit Organizations ◽  
Bounded Rationality ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Stable State ◽  
Evolutionary Strategies ◽  
Content Type ◽  
Trust Relationships

Purpose The purpose of this paper is to investigate the dynamics and evolution of trust in organizational cross alliances. Design/methodology/approach In alliances between corporations and nonprofit organizations, trust in decision-making is a dynamic process. Using the replicated dynamics model of evolutionary game theory, this paper provides a trust decision model and analyzes four scenarios under different parameters. A numerical simulation is developed to present an intuitive interpretation of the dynamic development of trust decisions and the effects of incentive and punishment mechanisms. Findings Under different parameters, bounded rationality and utilities result in different but stable evolutionary strategies; the initial probability of adopting a trust strategy leads directly to whether participants adopt the strategy when the system reaches stability after continued games; and incentive and punishment mechanisms can significantly reduce the initial probability of adopting a trust strategy where the system evolves to meet stable state needs. Practical implications The establishment of trust relationships is an important influence on the stable and coordinated development of an alliance. The proposed model can help the alliance build closer trust relationships and provide a theoretical basis for the design of the trust mechanism. Originality/value Incentive and punishment bound by some degree of trust are introduced to address the problems of trust decisions and their dynamics; the model created reflects the bounded rationality and utility of each game stage. Useful evolutionary stable strategies using different variables are proposed to address the decision-making problems of trust in cross alliances.

A dynamic evolutionary game model of web celebrity brand eWOM marketing control strategy

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mengjie Liao ◽  
Jian Zhang ◽  
Ruimei Wang
Keyword(s):  
Game Theory ◽  
Social Media ◽  
Evolutionary Game Theory ◽  
Government Policy ◽  
Evolutionary Game ◽  
Theoretical Research ◽  
Dynamic Visualization ◽  
Formal Approach ◽  
Content Type ◽  
Marketing Environment

PurposeThis paper aims to recognize whether government policy supervision or social network platform supervision can effectively promote the control of misconducts of web celebrity brand eWOM marketing and to identify the key factors influencing the unhealthy web celebrity marketing environment.Design/methodology/approachTheoretical research was employed to develop a practical approach for applying evolutionary game theory to eWOM marketing controlling strategies modeling via dynamic visualization, systematic simulation experiments.FindingsEvolutionary game theory combined with dynamic simulation modeling can provide a formal approach to understanding web celebrity brand eWOM marketing decision-making in social media, which can thus support the control of unhealthy web celebrity marketing environment. The results demonstrate that the reasonable control of social platform control costs may be more effective than the government policy on web celebrity fake brand eWOM marketing behaviors.Originality/valueThe study enriches the research on the management and control of eWOM marketing as well as provides guidance for the sustainable development of the web celebrity economy in social media.

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