Effect of nonlinear coefficient and edge weight on complex networks
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摘要: 在加权的无标度复杂网络中使用SIR模型,使用边权的函数f()来表示节点间的连接强度,以模拟现实中人们对于关系更亲密的人的信任度更高的情况. 现实生活中,谣言的传播者并不总是将谣言告知所有认识的人, 故引入Anurag Singh(2013)模型中的非线性传播指数以研究谣言在较为实际的加权复杂网络中的传播行为.本文讨论了f()和对于传播过程的一些影响, 发现在相关加权网络中,边权kk'在其函数f()的作用下和对于人群中听过谣言的人的比例r(t)的稳态值即r()共同产生影响, 并且也会影响谣言的爆发时间. 在研究中,引入f()和并未使修正后的传播模型有一个正的传播阈值c.Abstract: In this paper, standard SIR model of rumor In this paper, standard SIR model of rumor spreading is used in the weighting complex networks. The tie strength is expressed by the function of edge weight\textit f() in order to simulate the function between relationship and reliant interpersonal. In the practical scene, a node may only be contacted by some of its neighbors, so that the nonlinear rumor spread exponent of Anurag Singh (2013) is introduced, and the rumor spreading in complex networks is discussed. The effect of \textit f() and on the rumor threshold is discussed in the paper. It is found that the mean edge weightkk'together with its function\textit f() and are both effect the steady state value of r(t), that is \textitr(), which means the rate of people who heard the rumor in the crowd. And the explosion time is also effected by them. In the research, a positive tumor threshold c had not been found when the \textit f() and are introduced.
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Key words:
- rumor spreading /
- SIR model /
- weighting complex networks /
- nonlinear spreading
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