The small world yields the most effective information spreading
The small world yields the most effective information spreading
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小世界，最有效的信息传播
DOI：
10.1088/1367-2630/13/12/123005
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发表时间：
2011-12-02
影响因子：
3.3
通讯作者：
Zhou, Tao
中科院分区：
文献类型：
--
作者：
Lu, Linyuan;Chen, Duan-Bing;Zhou, Tao
通常使用统一的框架和类似的模型来分析信息和疾病的传播动态。在本文中，我们提出了一个模型来强调信息传播和流行病传播之间的本质区别，其中考虑了记忆效应、社会强化和接触的非冗余性。在某些条件下，信息在规则网络中的传播速度比在随机网络中更快、更广，这在一定程度上支持了最近关于网络社会传播的实验观察（Centola D 2010 Science 329 1194）。同时，仿真结果表明，当网络规模增大时，随机网络往往有利于有效传播。这对上述大规模系统实验的有效性提出了挑战。更重要的是，我们表明，通过在规则结构中引入一点随机性可以大大提高传播有效性，即小世界网络产生最有效的信息传播。这项工作提供了对本地集群在信息传播中的作用的见解。
The spreading dynamics of information and diseases are usually analyzed by using a unified framework and analogous models. In this paper, we propose a model to emphasize the essential difference between information spreading and epidemic spreading, where the memory effects, the social reinforcement and the non-redundancy of contacts are taken into account. Under certain conditions, the information spreads faster and broader in regular networks than in random networks, which to some extent supports the recent experimental observation of spreading in online society (Centola D 2010 Science 329 1194). At the same time, the simulation result indicates that the random networks tend to be favorable for effective spreading when the network size increases. This challenges the validity of the above-mentioned experiment for large-scale systems. More importantly, we show that the spreading effectiveness can be sharply enhanced by introducing a little randomness into the regular structure, namely the small-world networks yield the most effective information spreading. This work provides insights into the role of local clustering in information spreading.