Extracting the Core Structure of Social Networks Using (α, β)-Communities

Q3 Mathematics Internet Mathematics Pub Date : 2013-01-01 DOI:10.1080/15427951.2012.678187
Liaoruo Wang, J. Hopcroft, Jing He, Hongyu Liang, Supasorn Suwajanakorn
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引用次数: 13

Abstract

An (α, β)-community is a connected subgraph C with each vertex in C connected to at least β vertices of C (self-loops counted) and each vertex outside of C connected to at most α vertices of C (α<β). In this paper, we present a heuristic algorithm that in practice successfully finds a fundamental community structure. We also explore the structure of (α, β)-communities in various social networks. (α, β)-communities are well clustered into a small number of disjoint groups, and there are no isolated (α, β)-communities scattered between these groups. Two (α, β)-communities in the same group have significant overlap, while those in different groups have extremely small resemblance. A surprising core structure is discovered by taking the intersection of each group of massively overlapping (α, β)-communities. Further, similar experiments on random graphs demonstrate that the core structure found in many social networks is due to their underlying social structure, rather than to high-degree vertices or a particular degree distribution.
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利用(α, β)-社区提取社会网络核心结构
(α, β)-群落是连通子图C,其中C内的每个顶点至少连接C的β个顶点(自环计数),C外的每个顶点最多连接C的α个顶点(α<β)。在本文中,我们提出了一种启发式算法,在实践中成功地找到了一个基本的社区结构。我们还探讨了各种社会网络中(α, β)-社区的结构。(α, β)群落很好地聚集成少数不相交的类群,在这些类群之间没有孤立的(α, β)群落。同一类群内的两个(α, β)-群落具有显著的重叠,而不同类群间的相似性极小。一个令人惊讶的核心结构被发现通过采取每组大规模重叠(α, β)-社区的交集。此外,在随机图上进行的类似实验表明,在许多社会网络中发现的核心结构是由于其潜在的社会结构,而不是由于高度顶点或特定度分布。
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Internet Mathematics
Internet Mathematics Mathematics-Applied Mathematics
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