分层递阶的网络结构洞占据者挖掘及分析

Mining Hierarchical Structural Holes of the Network and Its Analysis

结构洞是在社会网络信息传播中占据重要位置的一类关键节点。据研究,5%的结构洞控制着50%的信息传播。学者们研究了单一粒度网络下结构洞的挖掘方法及分析,然而很多网络存在分层递阶的多粒度结构特性,对分层递阶网络的结构洞挖掘和分析具有现实意义。因此,该文提出了一种分层递阶网络的多粒度结构洞挖掘方法 HI-SH,并对不同粒度下的结构洞进行了分析。在该方法中,首先对网络进行多粒度社团划分,得到每一粒度下网络的社团;然后,根据两级信息传播理论,使用单一粒度下结构洞挖掘算法,挖掘每一粒度下top-k结构洞。在公用数据Topic16和真实数据上进行了实验,结果表明,网络的结构洞是动态变化的,单一粒度下的结构洞排名不能代表整个网络的结构洞排名。

In social networks,structural holes refer to a class of nodes which occupy the important position in the information diffusion.According to the study,5% of structural holes control 50% of the information diffusion.The researchers have studied how to mine structural holes under a single granularity,however,there are a lot of networks,whose structure with hierarchical multi-granularity.So,it is of great significance to mine and make an analysis of the structural holes of the network under the multi-granularity.In this paper,a method named HI-SH is proposed to mine multi-granularity structural holes of the network with hierarchical structure.Furthermore,some analysis of structural holes under the multi-granularity are also given based on this method.In this method,firstly,we detect the community of the network in each hierarchical granularity.Then,according to the theory of two-step information diffusion,structural holes mine algorithm is used to mine top-k structural holes in each granularity.Experiments on public data Topic16 and real data show that structural holes of the network are dynamical and structural holes ranking under single granularity can not represent the rank order all granularities of the network.