Print Email Facebook Twitter The aging effect in evolving scientific citation networks Title The aging effect in evolving scientific citation networks Author Hu, Feng (Qinghai Normal University; Ministry of Education Hangzhou; Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province) Ma, Lin (Hangzhou Normal University) Zhan, X. (TU Delft Multimedia Computing; Hangzhou Normal University) Zhou, Yinzuo (Hangzhou Normal University) Liu, Chuang (Hangzhou Normal University) Zhao, Haixing (Qinghai Normal University; Ministry of Education Hangzhou; Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province) Zhang, Zi Ke (Hangzhou Normal University; College of Media and International Culture) Date 2021 Abstract The study of citation networks is of interest to the scientific community. However, the underlying mechanism driving individual citation behavior remains imperfectly understood, despite the recent proliferation of quantitative research methods. Traditional network models normally use graph theory to consider articles as nodes and citations as pairwise relationships between them. In this paper, we propose an alternative evolutionary model based on hypergraph theory in which one hyperedge can have an arbitrary number of nodes, combined with an aging effect to reflect the temporal dynamics of scientific citation behavior. Both theoretical approximate solution and simulation analysis of the model are developed and validated using two benchmark datasets from different disciplines, i.e. publications of the American Physical Society (APS) and the Digital Bibliography & Library Project (DBLP). Further analysis indicates that the attraction of early publications will decay exponentially. Moreover, the experimental results show that the aging effect indeed has a significant influence on the description of collective citation patterns. Shedding light on the complex dynamics driving these mechanisms facilitates the understanding of the laws governing scientific evolution and the quantitative evaluation of scientific outputs. Subject Aging effectEvolutionHypergraph theoryScientific citation network To reference this document use: http://resolver.tudelft.nl/uuid:4fe313d7-af50-4adb-afb6-917df38308d7 DOI https://doi.org/10.1007/s11192-021-03929-8 ISSN 0138-9130 Source Scientometrics: an international journal for all quantitative aspects of the science of science, communication in science and science policy, 126 (5), 4297-4309 Part of collection Institutional Repository Document type journal article Rights © 2021 Feng Hu, Lin Ma, X. Zhan, Yinzuo Zhou, Chuang Liu, Haixing Zhao, Zi Ke Zhang Files PDF Hu2021_Article_TheAgingEf ... Scient.pdf 1.48 MB Close viewer /islandora/object/uuid:4fe313d7-af50-4adb-afb6-917df38308d7/datastream/OBJ/view