The epidemic network construction and immunization based on node strength

2018 ◽  
Vol 32 (26) ◽  
pp. 1850319 ◽  
Author(s):  
Fuzhong Nian ◽  
Longjing Wang ◽  
Zhongkai Dang
Keyword(s):  
Social Networks ◽  
Real World ◽  
Scale Free Network ◽  
Network Construction ◽  
The Real ◽  
Scale Free ◽  
Social Ability ◽  
The Social ◽  
Free Network

In this paper, a new spreading network was constructed and the corresponding immunizations were proposed. The social ability of individuals in the real human social networks was reflected by the node strength. The negativity and positivity degrees were also introduced. And the edge weights were calculated by the negativity and positivity degrees, respectively. Based on these concepts, a new asymmetric edge weights scale-free network which was more close to the real world was established. The comparing experiments indicate that the proposed immunization is priority to the acquaintance immunization, and close to the target immunization.

scholarly journals The Evolution of Price Competition Game on Complex Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Feng Jie Xie ◽  
Jing Shi
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Price Competition ◽  
Small World ◽  
Square Lattice ◽  
Small World Network ◽  
Scale Free Network ◽  
The Real ◽  
Scale Free ◽  
Free Network

The well-known “Bertrand paradox” describes a price competition game in which two competing firms reach an outcome where both charge a price equal to the marginal cost. The fact that the Bertrand paradox often goes against empirical evidences has intrigued many researchers. In this work, we study the game from a new theoretical perspective—an evolutionary game on complex networks. Three classic network models, square lattice, WS small-world network, and BA scale-free network, are used to describe the competitive relations among the firms which are bounded rational. The analysis result shows that full price keeping is one of the evolutionary equilibriums in a well-mixed interaction situation. Detailed experiment results indicate that the price-keeping phenomenon emerges in a square lattice, small-world network and scale-free network much more frequently than in a complete network which represents the well-mixed interaction situation. While the square lattice has little advantage in achieving full price keeping, the small-world network and the scale-free network exhibit a stronger capability in full price keeping than the complete network. This means that a complex competitive relation is a crucial factor for maintaining the price in the real world. Moreover, competition scale, original price, degree of cutting price, and demand sensitivity to price show a significant influence on price evolution on a complex network. The payoff scheme, which describes how each firm’s payoff is calculated in each round game, only influences the price evolution on the scale-free network. These results provide new and important insights for understanding price competition in the real world.

Optimal Nonlinear Pricing in Social Networks Under Asymmetric Network Information

2020 ◽  
Vol 68 (3) ◽  
pp. 818-833
Author(s):  
Yang Zhang ◽  
Ying-Ju Chen
Keyword(s):  
Social Networks ◽  
Nonlinear Pricing ◽  
Local Network ◽  
Solution Approach ◽  
Scale Free ◽  
Network Information ◽  
Pricing Decisions ◽  
Pricing Scheme ◽  
The Social ◽  
Free Network

How should a firm make pricing decisions in social networks when the customers hold in private their local network information? In “Optimal Nonlinear Pricing in Social Networks Under Asymmetric Network Information,” Zhang and Chen develop a solution approach based on calculus of variations and positive neighbor affiliation to tackle this problem. They show that the optimal pricing compromises the capitalization of the susceptibility to neighbor consumption with the motivation of one’s own consumption, which gives rise to a menu of quantity premium or quantity discount. In the Erdös and Rényi graph (a special case of the social network model in this paper), they find that the pricing scheme does not screen network positions; consequently, the firm can offer a simple uniform price. The authors also find that, in the context of two-way connections, the firm-optimal consumption becomes linear in customer degree in the scale-free network.

scholarly journals Effectiveness of Closure of Public Places with Time Delay in Disease Control

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Zhenggang Wang ◽  
Kwok Yip Szeto ◽  
Frederick Chi-Ching Leung
Keyword(s):  
Social Network ◽  
Time Delay ◽  
Disease Control ◽  
Sir Model ◽  
Scale Free Network ◽  
Public Places ◽  
Scale Free ◽  
The Social ◽  
Free Network ◽  
High Degree

SummaryA theoretical basis for the evaluation of the effciency of quarantine measure is developed in a SIR model with time delay. In this model, the effectiveness of the closure of public places such as schools in disease control, modeled as a high degree node in a social network, is evaluated by considering the effect of the time delay in the identification of the infected. In the context of the SIR model, the relation between the number of infectious individuals who are identified with time delay and then quarantined and those who are not identified and continue spreading the virus are investigated numerically. The social network for the simulation is modeled by a scale free network. Closure measures are applied to those infected nodes with high degrees. The effectiveness of the measure can be controlled by the present value of the critical degree K

Hub Agents Determine Collective Behavior

2015 ◽  
Vol 11 (02) ◽  
pp. 165-181
Author(s):  
Saori Iwanaga ◽  
Akira Namatame
Keyword(s):  
Social Network ◽  
Collective Behavior ◽  
Traffic Congestion ◽  
Scale Free Network ◽  
Collective Phenomena ◽  
Computing Technology ◽  
Scale Free ◽  
Cooperative Relationships ◽  
The Social ◽  
Free Network

There are growing interests for studying collective behavior including the dynamics of markets, the emergence of social norms and conventions and collective phenomena in daily life such as traffic congestion. In our previous work [Iwanaga and Namatame, Collective behavior and diverse social network, International Journal of Advancements in Computing Technology 4(22) (2012) 321–320], we showed that collective behavior in cooperative relationships is affected in the structure of the social network, the initial collective behavior and diversity of payoff parameter. In this paper, we focus on scale-free network and investigate the effect of number of interactions on collective behavior. And we found that choices of hub agents determine collective behavior.

The social costs of punishment

2012 ◽  
Vol 35 (1) ◽  
pp. 42-43 ◽  
Author(s):  
Pieter van den Berg ◽  
Lucas Molleman ◽  
Franz J. Weissing
Keyword(s):  
Social Networks ◽  
Real World ◽  
Cooperative Behavior ◽  
Social Costs ◽  
The Real ◽  
Lab Experiments ◽  
The Social ◽  
Direct Payments

AbstractLab experiments on punishment are of limited relevance for understanding cooperative behavior in the real world. In real interactions, punishment is not cheap, but the costs of punishment are of a different nature than in experiments. They do not correspond to direct payments or payoff deductions, but they arise from the repercussions punishment has on social networks and future interactions.

scholarly journals Modeling and Simulating Online Panic in an Epidemic Complexity System: An Agent-Based Approach

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Linjiang Guo ◽  
Yang Li ◽  
Dongfang Sheng
Keyword(s):  
Disease Outbreaks ◽  
Scale Free Network ◽  
Online Forums ◽  
Social Production ◽  
Social Responses ◽  
Agent Based ◽  
Scale Free ◽  
The Social ◽  
Free Network ◽  
The Impact

Following the outbreak of a disease, panic often spreads on online forums, which seriously affects normal economic operations as well as epidemic prevention procedures. Online panic is often manifested earlier than in the real world, leading to an aggravated social response from citizens. This paper conducts sentiment analysis on more than 80,000 comments about COVID-19 obtained from the Chinese Internet and identifies patterns within them. Based on this analysis, we propose an agent-based model consisting of two parts—a revised SEIR model to simulate an offline epidemic and a scale-free network to simulate the Internet community. This model is then used to analyze the effects of the social distancing policy. Assuming the existence of such a policy, online panic is simulated corresponding to different informatization levels. The results indicate that increased social informatization levels lead to substantial online panic during disease outbreaks. To reduce the economic impact of epidemics, we discuss different strategies for releasing information on the epidemic. Our conclusions indicate that announcing the number of daily new cases or the number of asymptomatic people following the peak of symptomatic infections could help to reduce the intensity of online panic and delay the peak of panic. In turn, this can be expected to keep social production more orderly and reduce the impact of social responses on the economy.

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