{"title":"Closeness centrality via the Condorcet principle","authors":"Oskar Skibski","doi":"10.1016/j.socnet.2023.01.005","DOIUrl":null,"url":null,"abstract":"<div><p>We provide a characterization of closeness centrality in the class of distance-based centralities. To this end, we introduce a natural property, called <em>majority comparison</em>, that states that out of two adjacent nodes the one closer to more nodes is more central. We prove that any distance-based centrality that satisfies this property gives the same ranking in every graph as closeness centrality. The axiom is inspired by the interpretation of the graph as an election in which nodes are both voters and candidates and their preferences are determined by the distances to the other nodes.</p></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"74 ","pages":"Pages 13-18"},"PeriodicalIF":2.9000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Networks","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378873323000059","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
引用次数: 3
Abstract
We provide a characterization of closeness centrality in the class of distance-based centralities. To this end, we introduce a natural property, called majority comparison, that states that out of two adjacent nodes the one closer to more nodes is more central. We prove that any distance-based centrality that satisfies this property gives the same ranking in every graph as closeness centrality. The axiom is inspired by the interpretation of the graph as an election in which nodes are both voters and candidates and their preferences are determined by the distances to the other nodes.
期刊介绍:
Social Networks is an interdisciplinary and international quarterly. It provides a common forum for representatives of anthropology, sociology, history, social psychology, political science, human geography, biology, economics, communications science and other disciplines who share an interest in the study of the empirical structure of social relations and associations that may be expressed in network form. It publishes both theoretical and substantive papers. Critical reviews of major theoretical or methodological approaches using the notion of networks in the analysis of social behaviour are also included, as are reviews of recent books dealing with social networks and social structure.