A Study on Interdisciplinary Structure of Big Data Research with Journal-Level Bibliographic-Coupling Analysis (학술지 단위 서지결합분석을 통한 빅데이터 연구분야의 학제적 구조에 관한 연구)

Boram Lee (이보람); Eunkyung Chung (정은경)

doi:10.3743/KOSIM.2016.33.3.133

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

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2016, 33(3), pp.133~154
DOI : 10.3743/KOSIM.2016.33.3.133
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : August 17, 2016
Accepted : September 5, 2016
Published : September 30, 2016

Boram Lee ¹, Eunkyung Chung ¹

¹이화여자대학교

Accredited

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

Citation status

* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

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

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

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

ABSTRACT

KEYWORDS

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KCI Citation Counts (9)

REFERENCES (32) * References for papers published after 2023 are currently being built.

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* References for papers published after 2023 are currently being built.