摘要翻译：
图顶点通常被组织成组，这些组似乎与图的其余部分相当独立，它们只与图的其余部分共享少数边，而组成员之间的关系更强，这表现在大量的相互连接上。这样的顶点群，或共同体，可以被认为是一个图的独立的区域。社区检测在社会学、生物学和计算机科学等学科中具有重要意义，这些学科的系统通常用图形表示。然而，这项任务是非常困难的，无论是在概念上，由于社区定义和区分不同分区的模糊性，还是在实际中，因为算法必须在指数级的大量分区中找到“好的”分区。其他复杂情况表现为可能出现的层次结构，即嵌套在较大社区内的社区，以及由于存在属于更多群体的节点，社区之间存在重叠。从计算机科学和社会学中使用的传统方法到统计物理学中发展起来的最新技术，所有这些方面都得到了详细的论述，并描述了许多方法。
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英文标题：
《Community Structure in Graphs》
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作者：
Santo Fortunato, Claudio Castellano
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最新提交年份：
2007
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分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Physics        物理学
二级分类：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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一级分类：Physics        物理学
二级分类：Computational Physics        计算物理学
分类描述：All aspects of computational science applied to physics.
应用于物理学的计算科学的各个方面。
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英文摘要：
  Graph vertices are often organized into groups that seem to live fairly independently of the rest of the graph, with which they share but a few edges, whereas the relationships between group members are stronger, as shown by the large number of mutual connections. Such groups of vertices, or communities, can be considered as independent compartments of a graph. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. The task is very hard, though, both conceptually, due to the ambiguity in the definition of community and in the discrimination of different partitions and practically, because algorithms must find ``good'' partitions among an exponentially large number of them. Other complications are represented by the possible occurrence of hierarchies, i.e. communities which are nested inside larger communities, and by the existence of overlaps between communities, due to the presence of nodes belonging to more groups. All these aspects are dealt with in some detail and many methods are described, from traditional approaches used in computer science and sociology to recent techniques developed mostly within statistical physics.
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PDF链接：
https://arxiv.org/pdf/712.2716