论文标题
合格：一种通心感的节点归因网络
Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks
论文作者
论文摘要
在社交网络分析中，揭示表征复杂网络的布线模式的同质/异质行为是研究节点属性的分类混合的重要任务。最近的著作强调了一种量化节点同质性的全球措施必然提供了一部分，经常欺骗的现实情况。在这项工作中，我们提出了一种新颖的措施，即合格，旨在通过提供以节点为中心的分类混合模式来克服这种限制。与迄今为止提出的措施不同，符合性被设计为途径感知，从而可以更详细地评估不同程度的分离对靶标的均电嵌入性的影响。对合成和真实数据的实验分析使我们可以观察到合格可以从节点归因的图中揭示出宝贵的见解。
Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached studying the assortative mixing of node attributes. Recent works underlined that a global measure to quantify node homophily necessarily provides a partial, often deceiving, picture of the reality. Moving from such literature, in this work, we propose a novel measure, namely Conformity, designed to overcome such limitation by providing a node-centric quantification of assortative mixing patterns. Differently from the measures proposed so far, Conformity is designed to be path-aware, thus allowing for a more detailed evaluation of the impact that nodes at different degrees of separations have on the homophilic embeddedness of a target. Experimental analysis on synthetic and real data allowed us to observe that Conformity can unveil valuable insights from node-attributed graphs.
