@article{ART002330551},
author={Chul Wan Kwak},
title={Subject Association Analysis of Big Data Studies: Using Co-citation Networks},
journal={Journal of the Korean Society for Information Management},
issn={1013-0799},
year={2018},
volume={35},
number={1},
pages={13-32},
doi={10.3743/KOSIM.2018.35.1.013}
TY - JOUR
AU - Chul Wan Kwak
TI - Subject Association Analysis of Big Data Studies: Using Co-citation Networks
JO - Journal of the Korean Society for Information Management
PY - 2018
VL - 35
IS - 1
PB - 한국정보관리학회
SP - 13
EP - 32
SN - 1013-0799
AB - The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into ‘professional type’, ‘general type’, ‘expanded type’ depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.
KW - big data;association analysis;co-citation networks;R program;academic information services
DO - 10.3743/KOSIM.2018.35.1.013
ER -
Chul Wan Kwak. (2018). Subject Association Analysis of Big Data Studies: Using Co-citation Networks. Journal of the Korean Society for Information Management, 35(1), 13-32.
Chul Wan Kwak. 2018, "Subject Association Analysis of Big Data Studies: Using Co-citation Networks", Journal of the Korean Society for Information Management, vol.35, no.1 pp.13-32. Available from: doi:10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak "Subject Association Analysis of Big Data Studies: Using Co-citation Networks" Journal of the Korean Society for Information Management 35.1 pp.13-32 (2018) : 13.
Chul Wan Kwak. Subject Association Analysis of Big Data Studies: Using Co-citation Networks. 2018; 35(1), 13-32. Available from: doi:10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak. "Subject Association Analysis of Big Data Studies: Using Co-citation Networks" Journal of the Korean Society for Information Management 35, no.1 (2018) : 13-32.doi: 10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak. Subject Association Analysis of Big Data Studies: Using Co-citation Networks. Journal of the Korean Society for Information Management, 35(1), 13-32. doi: 10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak. Subject Association Analysis of Big Data Studies: Using Co-citation Networks. Journal of the Korean Society for Information Management. 2018; 35(1) 13-32. doi: 10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak. Subject Association Analysis of Big Data Studies: Using Co-citation Networks. 2018; 35(1), 13-32. Available from: doi:10.3743/KOSIM.2018.35.1.013
Chul Wan Kwak. "Subject Association Analysis of Big Data Studies: Using Co-citation Networks" Journal of the Korean Society for Information Management 35, no.1 (2018) : 13-32.doi: 10.3743/KOSIM.2018.35.1.013
