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→背景和历史
20世纪90年代，在Paul Erdős和Alfréd Rényi发表了8篇关于随机图的著名论文之后，网络科学中的概率理论Probabilistic theory 作为图论的一个分支发展起来了。 对于[[社交网络]]social network来说，指数随机图模型或p* (是一个记号框架），用来表示在一个社交网络中连边在概率空间发生的概率。 网络概率结构的另一种替代表示方法是网络概率矩阵，它根据网络样本中边的历史信息来计算这条边在网络中出现的概率。
20世纪90年代，在Paul Erdős和Alfréd Rényi发表了8篇关于随机图的著名论文之后，网络科学中的概率理论Probabilistic theory 作为图论的一个分支发展起来了。 对于[[社交网络]]social network来说，指数随机图模型或p* (是一个记号框架），用来表示在一个社交网络中连边在概率空间发生的概率。 网络概率结构的另一种替代表示方法是网络概率矩阵，它根据网络样本中边的历史信息来计算这条边在网络中出现的概率。
[[用户:思无涯咿呀咿呀|思无涯咿呀咿呀]]（[[用户讨论:思无涯咿呀咿呀|讨论]]）概率理论Probabilistic theory，之所以没有翻译成概率论是因为概率论作为一个单独的学科是翻译成statistics，而这里特指的是网络科学里面的概率理论部分[[用户:思无涯咿呀咿呀|思无涯咿呀咿呀]]（[[用户讨论:思无涯咿呀咿呀|讨论]]）
[[用户:思无涯咿呀咿呀|思无涯咿呀咿呀]]（[[用户讨论:思无涯咿呀咿呀|讨论]]）概率理论Probabilistic theory，之所以没有翻译成概率论是因为概率论作为一个单独的学科是翻译成statistics，而这里特指的是网络科学里面的概率理论部分[[用户:思无涯咿呀咿呀|思无涯咿呀咿呀]]（[[用户讨论:思无涯咿呀咿呀|讨论]]）
In 1998, [[David Krackhardt]] and [[Kathleen Carley]] introduced the idea of a meta-network with the PCANS Model. They suggest that "all organizations are structured along these three domains, Individuals, Tasks, and Resources". Their paper introduced the concept that networks occur across multiple domains and that they are interrelated. This field has grown into another sub-discipline of network science called [[dynamic network analysis]].
In 1998, [[David Krackhardt]] and [[Kathleen Carley]] introduced the idea of a meta-network with the PCANS Model. They suggest that "all organizations are structured along these three domains, Individuals, Tasks, and Resources". Their paper introduced the concept that networks occur across multiple domains and that they are interrelated. This field has grown into another sub-discipline of network science called [[dynamic network analysis]].
In 1998, David Krackhardt and Kathleen Carley introduced the idea of a meta-network with the PCANS Model. They suggest that "all organizations are structured along these three domains, Individuals, Tasks, and Resources". Their paper introduced the concept that networks occur across multiple domains and that they are interrelated. This field has grown into another sub-discipline of network science called dynamic network analysis.
1998年，David Krackhardt和Kathleen Carley提出了用PCANS模型构建元网络meta-network的想法。 他们建议所有的组织都通过“个人、任务和资源”来构建。 他们的论文介绍了新的网络概念，即网络发生在多个领域的且相互关联。 这个领域已经发展也成为网络科学的另一个子学科，叫做[[动态网络分析]]dynamic network analysis。
More recently other network science efforts have focused on mathematically describing different network topologies. Duncan Watts reconciled empirical data on networks with mathematical representation, describing the [[small-world network]]. [[Albert-László Barabási]] and [[Reka Albert]] developed the [[scale-free network]] which is a loosely defined network topology that contains hub vertices with many connections, that grow in a way to maintain a constant ratio in the number of the connections versus all other nodes. Although many networks, such as the internet, appear to maintain this aspect, other networks have long tailed distributions of nodes that only approximate scale free ratios.
More recently other network science efforts have focused on mathematically describing different network topologies. Duncan Watts reconciled empirical data on networks with mathematical representation, describing the [[small-world network]]. [[Albert-László Barabási]] and [[Reka Albert]] developed the [[scale-free network]] which is a loosely defined network topology that contains hub vertices with many connections, that grow in a way to maintain a constant ratio in the number of the connections versus all other nodes. Although many networks, such as the internet, appear to maintain this aspect, other networks have long tailed distributions of nodes that only approximate scale free ratios.
More recently other network science efforts have focused on mathematically describing different network topologies. Duncan Watts reconciled empirical data on networks with mathematical representation, describing the small-world network. Albert-László Barabási and Reka Albert developed the scale-free network which is a loosely defined network topology that contains hub vertices with many connections, that grow in a way to maintain a constant ratio in the number of the connections versus all other nodes. Although many networks, such as the internet, appear to maintain this aspect, other networks have long tailed distributions of nodes that only approximate scale free ratios.
最近其他网络科学的研究致力于用数学的方式描述不同网络的拓扑结构。[[邓肯·瓦茨]]Duncan Watts 将网络上的经验数据与数学表达相结合，描述了小世界网络。 [[艾伯特-拉斯洛·巴拉巴西 Albert-László Barabási]] 和 [[Reka Albert]]发现了无标度网络，这是一个定义松散的网络拓扑网络，它包含有许多连接的枢纽顶点，这些连接以一种保持连接数量与所有其他节点数量之间恒定比率的方式增长。尽管许多网络，比如互联网，似乎保持了这一点，但是其他网络的节点分布长尾分布仅仅接近无标度比例。
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