Node Attitude Aware Information Dissemination Model Based on Evolutionary Game in Social Networks

Author(s):  
Hongcheng Huang ◽  
Tingting Wang ◽  
Min Hu ◽  
Mengyuan Dong ◽  
Licheng Lai
2019 ◽  
Vol 30 (11) ◽  
pp. 1950094 ◽  
Author(s):  
Jianye Yu ◽  
Junjie Lv ◽  
Yuanzhuo Wang ◽  
Jingyuan Li

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Qing Sun ◽  
Zhong Yao

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.


2020 ◽  
Author(s):  
Haiming Wu ◽  
Ruigang Wang ◽  
Lixia Jia ◽  
Likui Feng ◽  
Xu Zhou

Abstract Social network has gradually become the mainstream way for people to obtain and interact with information. The study on the law of information dissemination in social networks is of great significance to enterprise marketing, public opinion control and social recommendation. This paper puts forward a method that use multi-dimensional node influence and epidemic model to illustrate the causes and rules of information dissemination in social networks. Firstly, based on the multiple linear regression model, a measurement method of node influence is proposed from three dimensions: topology, user interaction behavior and information content. Then, taking the node influence as the cause of state transition, the information dissemination model based on the epidemic model is constructed, and the multidimensional factors affecting the information dissemination are analyzed. Meanwhile, the information dissemination trend in social networks is described.


Author(s):  
Yunpeng Xiao ◽  
Wen Li ◽  
Shuai Qiang ◽  
Qian Li ◽  
Hanchun Xiao ◽  
...  

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