Department of Information Science, Cornell University, Ithaca, NY, USA.
Department of Computer Science, Cornell University, Ithaca, NY, USA.
Sci Rep. 2021 Jun 25;11(1):13360. doi: 10.1038/s41598-021-92719-6.
Homophily-the tendency of nodes to connect to others of the same type-is a central issue in the study of networks. Here we take a local view of homophily, defining notions of first-order homophily of a node (its individual tendency to link to similar others) and second-order homophily of a node (the aggregate first-order homophily of its neighbors). Through this view, we find a surprising result for homophily values that applies with only minimal assumptions on the graph topology. It can be phrased most simply as "in a graph of red and blue nodes, red friends of red nodes are on average more homophilous than red friends of blue nodes". This gap in averages defies simple intuitive explanations, applies to globally heterophilous and homophilous networks and is reminiscent of but structually distinct from the Friendship Paradox. The existence of this gap suggests intrinsic biases in homophily measurements between groups, and hence is relevant to empirical studies of homophily in networks.
同配性——节点倾向于与同类型的其他节点连接——是网络研究中的一个核心问题。在这里,我们从局部视角来看同配性,定义了节点的一阶同配性(其与相似节点连接的个体倾向)和节点的二阶同配性(其邻居的一阶同配性总和)。通过这种视角,我们发现了一个令人惊讶的同配性值结果,该结果仅在图拓扑结构的最小假设下适用。它可以用最简单的方式表述为“在一个由红色和蓝色节点组成的图中,红色节点的红色朋友的同配性平均值高于蓝色节点的红色朋友的同配性平均值”。这种平均值的差距违背了简单的直观解释,适用于全局异配性和同配性网络,并且让人联想到但结构上不同于友谊悖论。这种差距的存在表明,在群体之间的同配性测量中存在内在偏见,因此与网络中同配性的实证研究相关。