Altmetrics视角下个体文献的知识扩散:模型、测量与特征

IF 1.8 4区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Information Science Pub Date : 2023-05-16 DOI:10.1177/01655515231174387
Jundong Zhang, Jia-lin Hou
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引用次数: 0

摘要

本文研究了网络社交媒体对知识传播的影响。本文建立了一个SIS(易感-传染-易感)模型,从Altmetrics的角度追踪知识传播,并确定了个体文献知识传播的合适模型。基于从PLoS ONE数据库收集的数据,计算了每篇论文的转移概率,并使用K-means算法根据转移概率将论文分为六组。本文从Altmetrics的角度探讨了转移概率的影响,并总结了各组知识传播模式的异同。研究结果表明,SIS模型可以从Altmetrics的角度描述单个文献的知识扩散。此外,本文提出的分类方法也可用于未来的情报研究。此外,本文还为知识传播和在线平台的从业者做出了贡献。
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Knowledge diffusion for individual literature from the perspective of Altmetrics: Models, measurement and features
This article studies the effect of online social media on knowledge diffusion. In this article, an SIS (Susceptible–Infectious–Susceptible) model was established to chase the knowledge diffusion and identify the proper model for knowledge diffusion of individual literature from the perspective of Altmetrics. Based on the data collected from the PLoS ONE database, the transition probabilities of each paper were calculated, and the papers were divided into six groups according to the transition probabilities using a K-means algorithm. This article explores the impacts of transition probabilities and summarises the similarities and differences of the patterns of knowledge diffusion of each group from the perspective of Altmetrics. Research results showed that the SIS model could be used to describe the knowledge diffusion of individual literature from the perspective of Altmetrics. Besides, the classification method proposed in this article could also be applied in future informetric research. In addition, this article also contributes to the practitioners of knowledge diffusion and online platforms.
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来源期刊
Journal of Information Science
Journal of Information Science 工程技术-计算机:信息系统
CiteScore
6.80
自引率
8.30%
发文量
121
审稿时长
4 months
期刊介绍: The Journal of Information Science is a peer-reviewed international journal of high repute covering topics of interest to all those researching and working in the sciences of information and knowledge management. The Editors welcome material on any aspect of information science theory, policy, application or practice that will advance thinking in the field.
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