{"title":"Use of aggregated relational data in agent-based modeling","authors":"Yunsub Lee , Xinwei Xu","doi":"10.1016/j.socnet.2025.09.004","DOIUrl":null,"url":null,"abstract":"<div><div>Aggregated relational data (ARD) provides valuable information for inferring structural features of personal social networks at scale. Following recent ARD studies, we suggest a formal parameter for agent-based modeling (ABM) that helps reflect multiple structural features of extended social networks (e.g., size; variation; distribution) and apply it to a widely known classic ABM—Axelrod’s cultural dynamic model. Results show that when incorporating realistic network features estimated from ARD, the model generates outcomes substantially different from its original results. Our study highlights ARD's potential to enrich ABM in reflecting more realistic networks that better connect micro-processes with macro-phenomena.</div></div>","PeriodicalId":48353,"journal":{"name":"Social Networks","volume":"84 ","pages":"Pages 164-179"},"PeriodicalIF":2.4000,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Networks","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378873325000668","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: 0
Abstract
Aggregated relational data (ARD) provides valuable information for inferring structural features of personal social networks at scale. Following recent ARD studies, we suggest a formal parameter for agent-based modeling (ABM) that helps reflect multiple structural features of extended social networks (e.g., size; variation; distribution) and apply it to a widely known classic ABM—Axelrod’s cultural dynamic model. Results show that when incorporating realistic network features estimated from ARD, the model generates outcomes substantially different from its original results. Our study highlights ARD's potential to enrich ABM in reflecting more realistic networks that better connect micro-processes with macro-phenomena.
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.