{"title":"The Evolution of Big Data in Knowledge Management: A Bibliometric Analysis","authors":"Tuğba Karaboğa, Yasin Şehitoğlu, H. Karaboğa","doi":"10.15612/bd.2022.645","DOIUrl":null,"url":null,"abstract":"Recently, the close relationship between big data and knowledge management has become one of the important agendas of businesses. The aim of this study is to systematize the literature on big data and knowledge management from a bibliometric perspective and to create a general framework for the past, present and future of the field. The present study examined 622 papers acquired from the Clarivate Analytics Web of Science (WoS) Core Collection database between 2013 and 2020. The results showed that the annual growth rate of the relevant field was found to be 42.9% indicating a higher popularity among researchers. China and USA are home to the most productive authors and institutions in the field. Also, country collaboration network, institutional co-authorship network, co-word network and co-citation network are given to present the intellectual structure of the field. This study is useful to understand leading trends in the field in terms of the most influential authors, institutions and countries, the most productive journals, the most frequent keywords, the collaboration networks and the co-citation networks. To the best of researchers’ knowledge, this study is the first bibliometric examination attempt to understand the flow at the intersection of big data and knowledge management over time.","PeriodicalId":38318,"journal":{"name":"Bilgi Dunyasi","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bilgi Dunyasi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15612/bd.2022.645","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, the close relationship between big data and knowledge management has become one of the important agendas of businesses. The aim of this study is to systematize the literature on big data and knowledge management from a bibliometric perspective and to create a general framework for the past, present and future of the field. The present study examined 622 papers acquired from the Clarivate Analytics Web of Science (WoS) Core Collection database between 2013 and 2020. The results showed that the annual growth rate of the relevant field was found to be 42.9% indicating a higher popularity among researchers. China and USA are home to the most productive authors and institutions in the field. Also, country collaboration network, institutional co-authorship network, co-word network and co-citation network are given to present the intellectual structure of the field. This study is useful to understand leading trends in the field in terms of the most influential authors, institutions and countries, the most productive journals, the most frequent keywords, the collaboration networks and the co-citation networks. To the best of researchers’ knowledge, this study is the first bibliometric examination attempt to understand the flow at the intersection of big data and knowledge management over time.
近年来,大数据与知识管理的密切关系已成为企业的重要议程之一。本研究的目的是从文献计量学的角度对大数据和知识管理的文献进行系统化,并为该领域的过去、现在和未来创建一个总体框架。本研究分析了2013年至2020年间从Clarivate Analytics Web of Science (WoS) Core Collection数据库中获得的622篇论文。结果显示,相关领域的年增长率为42.9%,表明研究人员对相关领域的关注度较高。中国和美国是该领域最多产的作者和机构的所在地。并以国家合作网络、机构合著网络、共词网络和共引网络为例,介绍了该领域的知识结构。该研究有助于了解该领域在最具影响力的作者、机构和国家、最高产期刊、最常用关键词、合作网络和共引网络等方面的领先趋势。据研究人员所知,这项研究是第一次尝试通过文献计量学检验来理解大数据和知识管理的交叉流动。