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http://dx.doi.org/10.3743/KOSIM.2016.33.3.133

A Study on Interdisciplinary Structure of Big Data Research with Journal-Level Bibliographic-Coupling Analysis  

Lee, Boram (이화여자대학교 일반대학원 문헌정보학과)
Chung, EunKyung (이화여자대학교 사회과학대학 문헌정보학 전공)
Publication Information
Journal of the Korean Society for information Management / v.33, no.3, 2016 , pp. 133-154 More about this Journal
Abstract
Interdisciplinary approach has been recognized as one of key strategies to address various and complex research problems in modern science. The purpose of this study is to investigate the interdisciplinary characteristics and structure of the field of big data. Among the 1,083 journals related to the field of big data, multiple Subject Categories (SC) from the Web of Science were assigned to 420 journals (38.8%) and 239 journals (22.1%) were assigned with the SCs from different fields. These results show that the field of big data indicates the characteristics of interdisciplinarity. In addition, through bibliographic coupling network analysis of top 56 journals, 10 clusters in the network were recognized. Among the 10 clusters, 7 clusters were from computer science field focusing on technical aspects such as storing, processing and analyzing the data. The results of cluster analysis also identified multiple research works of analyzing and utilizing big data in various fields such as science & technology, engineering, communication, law, geography, bio-engineering and etc. Finally, with measuring three types of centrality (betweenness centrality, nearest centrality, triangle betweenness centrality) of journals, computer science journals appeared to have strong impact and subjective relations to other fields in the network.
Keywords
big data; interdisciplinarity; bibliographic coupling analysis; network analysis;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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