论文标题
量化网络中的中尺度结构的存在/不存在
Quantifying the presence/absence of meso-scale structures in networks
论文作者
论文摘要
中尺度结构是网络特征，其中具有相似属性的节点被分组在一起而不是单独处理。在这项工作中，我们提供了三种此类结构的形式和数学定义：分类社区，分离性社区和核心周围。然后，我们利用这些定义和贝叶斯框架来量化网络中每个结构的存在/不存在。这允许有关网络结构以及组标签和边缘概率的不确定性估计的概率语句。该方法应用于现实世界网络，对众所周知的网络数据集产生挑衅性的结果。
Meso-scale structures are network features where nodes with similar properties are grouped together instead of being treated individually. In this work, we provide formal and mathematical definitions of three such structures: assortative communities, disassortative communities and core-periphery. We then leverage these definitions and a Bayesian framework to quantify the presence/absence of each structure in a network. This allows for probabilistic statements about the network structure as well as uncertainty estimates of the group labels and edge probabilities. The method is applied to real-world networks, yielding provocative results about well-known network data sets.
