Mechanism analysis of competitive information asynchronous dissemination on social networks

2019 ◽  
Vol 30 (11) ◽  
pp. 1950094 ◽  
Author(s):  
Jianye Yu ◽  
Junjie Lv ◽  
Yuanzhuo Wang ◽  
Jingyuan Li
Keyword(s):  
Social Networks ◽  
Information Diffusion ◽  
Information Dissemination ◽  
Evolutionary Game ◽  
Real Data ◽  
Game Model ◽  
Mechanism Analysis ◽  
Sina Weibo ◽  
Human Behaviors ◽  
Information Spread

Information dissemination groups, especially those disseminating the same kind of information such as advertising, product promotion, etc., compete with each other when their information spread on social networks. Most of the existing methods analyze the dissemination mechanism mainly upon the information itself without considering human characteristics, e.g. relation networks, cooperation/defection, etc. In this paper, we introduce a framework of social evolutionary game (SEG) to investigate the influence of human behaviors in competitive information dissemination. Coordination game is applied to represent human behaviors in the competition of asynchronous information diffusion. We perform a series of simulations through a specific game model to analyze the mechanism and factors of information diffusion, and show that when the benefits of competitive information is around 1.2 times of the original one, it can compensate the loss of reputation caused by the change of strategy. Furthermore, through experiments on a dataset of two films on Sina Weibo, we described the mechanism of competition evolution over real data of social network, and validated the effectiveness of our model.

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.

scholarly journals Intelligent Prediction of Private Information Diffusion in Social Networks

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 719 ◽  
Author(s):  
Yangyang Li ◽  
Hao Jin ◽  
Xiangyi Yu ◽  
Haiyong Xie ◽  
Yabin Xu ◽  
...  
Keyword(s):  
Social Networks ◽  
Private Information ◽  
Information Diffusion ◽  
Social Impact ◽  
Information Leakage ◽  
Prediction Method ◽  
Data Set ◽  
Sina Weibo ◽  
Critical Paths ◽  
The Impact

In the information age, leaked private information may cause significant physical and mental harm to the relevant parties, leading to a negative social impact. In order to effectively evaluate the impact of such information leakage in today’s social networks, it is necessary to accurately predict the scope and depth of private information diffusion. By doing so, it would be feasible to prevent and control the improper spread and diffusion of private information. In this paper, we propose an intelligent prediction method for private information diffusion in social networks based on comprehensive data analysis. We choose Sina Weibo, one of the most prominent social networks in China, to study. Firstly, a prediction model of message forwarding behavior is established by analyzing the characteristic factors that influence the forwarding behavior of the micro-blog users. Then the influence of users is calculated based on the interaction time and topological structure of users relationship, and the diffusion critical paths are identified. Finally, through the user forwarding probability transmission, we determine the micro-blog diffusion cut-off conditions. The simulation results on Sina Weibo data set show that the prediction accuracy is 86.9%, which indicates that our method is efficient to predict the message diffusion in real-world social networks.

scholarly journals Evolutionary Game Analysis of Competitive Information Dissemination on Social Networks: An Agent-Based Computational Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Qing Sun ◽  
Zhong Yao
Keyword(s):  
Social Networks ◽  
Information Dissemination ◽  
Evolutionary Game ◽  
Theoretic Model ◽  
Game Analysis ◽  
Agent Based ◽  
Related Information ◽  
Game Theoretic ◽  
Adoption And Diffusion ◽  
Information Adoption

Social networks are formed by individuals, in which personalities, utility functions, and interaction rules are made as close to reality as possible. Taking the competitive product-related information as a case, we proposed a game-theoretic model for competitive information dissemination in social networks. The model is presented to explain how human factors impact competitive information dissemination which is described as the dynamic of a coordination game and players’ payoff is defined by a utility function. Then we design a computational system that integrates the agent, the evolutionary game, and the social network. The approach can help to visualize the evolution of % of competitive information adoption and diffusion, grasp the dynamic evolution features in information adoption game over time, and explore microlevel interactions among users in different network structure under various scenarios. We discuss several scenarios to analyze the influence of several factors on the dissemination of competitive information, ranging from personality of individuals to structure of networks.

scholarly journals PUEGM: A Method of User Revenue Selection Based on a Publisher-User Evolutionary Game Model for Mobile Crowdsensing

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2927
Author(s):  
Zihao Shao ◽  
Huiqiang Wang ◽  
Guangsheng Feng
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Low Cost ◽  
Evolutionary Game ◽  
Real Data ◽  
Quality Data ◽  
Game Model ◽  
Mobile Crowdsensing ◽  
Data Quality Assessment ◽  
Selection Of

Mobile crowdsensing (MCS) is a way to use social resources to solve high-precision environmental awareness problems in real time. Publishers hope to collect as much sensed data as possible at a relatively low cost, while users want to earn more revenue at a low cost. Low-quality data will reduce the efficiency of MCS and lead to a loss of revenue. However, existing work lacks research on the selection of user revenue under the premise of ensuring data quality. In this paper, we propose a Publisher-User Evolutionary Game Model (PUEGM) and a revenue selection method to solve the evolutionary stable equilibrium problem based on non-cooperative evolutionary game theory. Firstly, the choice of user revenue is modeled as a Publisher-User Evolutionary Game Model. Secondly, based on the error-elimination decision theory, we combine a data quality assessment algorithm in the PUEGM, which aims to remove low-quality data and improve the overall quality of user data. Finally, the optimal user revenue strategy under different conditions is obtained from the evolutionary stability strategy (ESS) solution and stability analysis. In order to verify the efficiency of the proposed solutions, extensive experiments using some real data sets are conducted. The experimental results demonstrate that our proposed method has high accuracy of data quality assessment and a reasonable selection of user revenue.

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.

Incentive evolutionary game model for opportunistic social networks

2020 ◽  
Vol 102 ◽  
pp. 14-29 ◽  
Author(s):  
Eric Ke Wang ◽  
Chien-Ming Chen ◽  
Siu Ming Yiu ◽  
Mohammad Mehedi Hassan ◽  
Majed Alrubaian ◽  
...  
Keyword(s):  
Social Networks ◽  
Evolutionary Game ◽  
Game Model

scholarly journals Influence of We Media Information Dissemination on Public Emotional Cognition and Behavior under Government Responsibility Constraint

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Rongjian Xie ◽  
Dongju Liu ◽  
Yucai Jia ◽  
Peiyun Zhang
Keyword(s):  
Information Dissemination ◽  
Chaotic Behavior ◽  
Evolutionary Game ◽  
Pareto Optimum ◽  
Game Model ◽  
Government Responsibility ◽  
Governance System ◽  
Research Results ◽  
The Government ◽  
And Control

In recent years, We Media’s chaotic behavior has emerged one after another. How to properly supervise We Media and effectively manage its violations has become an urgent problem in the process of national governance system and governance capacity building. From the three aspects of opportunity, motivation, and control methods, this paper analyzes the relevant stakeholders and their relationships in the process of We Media information dissemination. It constructs a tripartite evolutionary game model of government, We Media, and public participation, which focuses on the analysis of the equilibrium point of the game model and carries out simulation experiments to explore the influence of government responsibility constraints on the evolution results. The research results show that government regulation plays an important role in restricting We Media’s information release. When the government's willingness to regulate increases, We Media will be punished more if it violates rules. In order to reduce the cost of punishment and other factors, We Media will reduce the willingness to violate the rules. After the occurrence of social hot events, the public is more willing to be guided by positive information from We Media, prompting the government to choose strict supervision strategies, effectively reducing the violations of We Media and achieving the Pareto optimum. According to the research results, this paper puts forward reasonable countermeasures to realize the comprehensive governance pattern of noncompliance of We Media and correct guidance of public emotional cognitive behavior under responsibility constraints. The research results provide theoretical support and decision-making basis for We Media information management and control.

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