{"title":"Knowledge diffusion for individual literature from the perspective of Altmetrics: Models, measurement and features","authors":"Jundong Zhang, Jia-lin Hou","doi":"10.1177/01655515231174387","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/01655515231174387","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.