{"title":"The attention inequality of scientists: A core-periphery structure perspective","authors":"Haoyang Wang , Win-bin Huang , Yi Bu","doi":"10.1016/j.ipm.2025.104170","DOIUrl":null,"url":null,"abstract":"<div><div>This study investigates the dynamics of scientific attention within author citation networks, utilizing the Microsoft Academic Graph dataset. Three author citation networks were constructed within the domains of nanoscience, chemical physics, and human-computer interaction. We apply analytical measurements to reveal core-periphery structures, indicating a growing disparity in scientific interactions. Our analysis highlights a concerning trend: while connections among prominent authors are strengthening, interactions among “ordinary” scientists remain relatively weak. This trend is further corroborated by the application of the network percolation method. After removing the prominent authors in the citation networks, multilayered and complex relationships among authors are revealed. We observe a decreasing trend of connection strength among relatively “ordinary” authors. The observed inequality of attention raises significant concerns about neglecting diverse voices within the scientific community. In response to these phenomena, our research emphasizes the importance of cultivating an inclusive scientific environment for early-career and underrepresented scholars, aiming for long-term sustainability in the scientific community.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 4","pages":"Article 104170"},"PeriodicalIF":7.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing & Management","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306457325001116","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the dynamics of scientific attention within author citation networks, utilizing the Microsoft Academic Graph dataset. Three author citation networks were constructed within the domains of nanoscience, chemical physics, and human-computer interaction. We apply analytical measurements to reveal core-periphery structures, indicating a growing disparity in scientific interactions. Our analysis highlights a concerning trend: while connections among prominent authors are strengthening, interactions among “ordinary” scientists remain relatively weak. This trend is further corroborated by the application of the network percolation method. After removing the prominent authors in the citation networks, multilayered and complex relationships among authors are revealed. We observe a decreasing trend of connection strength among relatively “ordinary” authors. The observed inequality of attention raises significant concerns about neglecting diverse voices within the scientific community. In response to these phenomena, our research emphasizes the importance of cultivating an inclusive scientific environment for early-career and underrepresented scholars, aiming for long-term sustainability in the scientific community.
期刊介绍:
Information Processing and Management is dedicated to publishing cutting-edge original research at the convergence of computing and information science. Our scope encompasses theory, methods, and applications across various domains, including advertising, business, health, information science, information technology marketing, and social computing.
We aim to cater to the interests of both primary researchers and practitioners by offering an effective platform for the timely dissemination of advanced and topical issues in this interdisciplinary field. The journal places particular emphasis on original research articles, research survey articles, research method articles, and articles addressing critical applications of research. Join us in advancing knowledge and innovation at the intersection of computing and information science.