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A novel model for social networks

机译:一种新颖的社交网络模型

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摘要

A number of recent studies on social networks are based on a characteristic which includes assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model which satisfies all the above characteristics is developed. In addition, this model facilitates interaction between various communities. This model gives very high clustering coefficient by retaining the asymptotically scale-free degree distribution. Here the community structure is raised from a mixture of random attachment and implicit preferential attachment. In addition to earlier works which only considered Neighbour of Initial Contact (NIC) as implicit preferential contact, we have considered Neighbour of Neighbour of Initial Contact (NNIC) also. This model supports the occurrence of a contact between two Initial contacts if the new vertex chooses more than one initial contacts. This ultimately will develop a complex social network rather than the one that was taken as basic reference.
机译:最近对社交网络的许多研究都基于一个特征,包括分类混合,高聚类,平均路径长度短,程度分布广泛以及社区结构的存在。在此,开发出满足上述所有特征的模型。此外,该模型还促进了各个社区之间的互动。该模型通过保留渐近的无标度分布来提供非常高的聚类系数。在这里,社区结构是由随机依附和隐性优先依附的混合产生的。除了早期的工作仅将初始联系人的邻居(NIC)视为隐式优先联系人之外,我们还考虑了初始联系人的邻居(NNIC)的邻居。如果新顶点选择多个初始接触,则此模型支持在两个初始接触之间发生接触。这最终将建立一个复杂的社交网络,而不是作为基础参考的社交网络。

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