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Complex networks: Most larger social networks display features of social complexity, which involves substantial non-trivial features of network topology, with patterns of complex connections between elements that are neither purely regular nor purely random (see, complexity science, dynamical system and chaos theory), as do biological, and technological networks. Such complex network features include a heavy tail in the degree distribution, a high clustering coefficient, assortativity or disassortativity among vertices, community structure (see stochastic block model), and hierarchical structure. In the case of agency-directed networks these features also include reciprocity, triad significance profile (TSP, see network motif), and other features. In contrast, many of the mathematical models of networks that have been studied in the past, such as lattices and random graphs, do not show these features.

Complex networks: Most larger social networks display features of social complexity, which involves substantial non-trivial features of network topology, with patterns of complex connections between elements that are neither purely regular nor purely random (see, complexity science, dynamical system and chaos theory), as do biological, and technological networks. Such complex network features include a heavy tail in the degree distribution, a high clustering coefficient, assortativity or disassortativity among vertices, community structure (see stochastic block model), and hierarchical structure. In the case of agency-directed networks these features also include reciprocity, triad significance profile (TSP, see network motif), and other features. In contrast, many of the mathematical models of networks that have been studied in the past, such as lattices and random graphs, do not show these features.

复杂网络: 大多数较大的社会网络呈现出社会复杂性的特征，包括'''<font color="#ff8000">网络拓扑 Network Topology</font>'''的大量非平凡特征，以及既不完全规则也不完全随机的元素之间的复杂连接模式（见[[复杂性科学]]、[[动力系统]]和[[混沌理论]]），生物和技术网络也是如此。这些复杂的网络特征包括度分布的重尾、高集聚系数、顶点之间的'''<font color="#ff8000">同配性 Assortativity</font>'''或非同配性、社区结构（见'''<font color="#ff8000">随机分块模型 Stochastic Block Model</font>'''）和层次结构。在主体导向网络的情况下，这些特征还包括互惠性、<font color="#32CD32">三重显著性特征</font>（TSP，见网络基序）及其他。相比之下，许多过去研究过的网络数学模型，如格和'''<font color="#ff8000">随机图 Random Graph</font>'''，并没有表现出这些特征。

复杂网络: 大多数较大的社会网络呈现出社会复杂性的特征，包括'''<font color="#ff8000">网络拓扑 Network Topology</font>'''的大量非平凡特征，以及既不完全规则也不完全随机的元素之间的复杂连接模式（见[[复杂性科学]]、[[动力系统]]和[[混沌理论]]），生物和技术网络也是如此。这些复杂的网络特征包括度分布的重尾、高集聚系数、顶点之间的'''<font color="#ff8000">同配性 Assortativity</font>'''或非同配性、社区结构（见'''<font color="#ff8000">随机分块模型 Stochastic Block Model</font>'''）和层次结构。在主体导向网络的情况下，这些特征还包括互惠性、'''<font color="#32CD32">三重显著性特征</font>'''（TSP，见网络基序）及其他。相比之下，许多过去研究过的网络数学模型，如格和'''<font color="#ff8000">随机图 Random Graph</font>'''，并没有表现出这些特征。

* [[Bibliography of sociology]] 社会学参考书目

* [[Bibliography of sociology]] 社会学参考书目