Coupling effect of nodes popularity and similarity on social network persistence.
Coupling effect of nodes popularity and similarity on social network persistence.
复制标题
节点流行度和相似度对社交网络持久性的耦合作用
DOI：
10.1038/srep42956
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发表时间：
2017-02-21
影响因子：
4.6
通讯作者：
Min Y
中科院分区：
文献类型：
--
作者：
Jin X;Jin C;Huang J;Min Y
网络鲁棒性表示网络承受故障和扰动的能力。在社会网络中，个体活动的维持，也称为持久性，对于理解鲁棒性非常重要。以前的研究通常考虑预先生成的网络结构的持久性；而在社会网络中，网络结构随着现有个体的级联不活动而增长。在这里，我们通过在共同进化模型下对节点进行分析来解决这一挑战，该模型描述了三种网络增长模式下的个体活动变化：遵循节点受欢迎程度、相似性或均匀随机的降序。研究表明，当节点具有较高的自发活动时，流行优先的增长模式获得了高度持久的网络；否则，在自发活动较低的情况下，相似优先模式效果更好。此外，在短时间内连续加入相似节点，并混合少数高人气节点的复合增长模式，可获得最高的持续性。因此，节点相似性对于持久的社交网络至关重要，而适当地将流行度与相似性耦合可以进一步优化持久性。这表明节点活动的演变不仅取决于网络拓扑，还取决于它们的连接类型。
Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.