Centrality is a foundational concept in network analysis that captures the centralizing tendency of a graph. In this talk, we introduce several measures of hypergraph centrality and, from the perspective of extremal set theory, define an index based on the sum of sizes of intersection. Using this index, we compare the intersection strength of families with fixed size, and obtain a quantitative version of the Erdős–Ko–Rado theorem.

黄苏闽，南京信息工程大学数学与统计学院讲师。2025年毕业于厦门大学数学科学学院，师从钱建国教授。主要从事极值图论、极值集合论的研究，相关成果发表于 J. Combin. Theory A, Discrete Math. 等期刊.