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  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

ISSN : 1013-0799

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Vol.40 No.4

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Analyzing the Main Paths and Intellectual Structure of the Data Literacy Research Domain

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2023, v.40 no.4, pp.403-428
https://doi.org/10.3743/KOSIM.2023.40.4.403
Jae Yun Lee (Myongji University)
Lee, J. Y. (2023). Analyzing the Main Paths and Intellectual Structure of the Data Literacy Research Domain. Journal of the Korean Society for Information Management, 40(4), 403-428, https://doi.org/10.3743/KOSIM.2023.40.4.403

Abstract

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

keywords
data literacy, critical data literacy, main path analysis, PageRank main path analysis, intellectual structure analysis
Submission Date
2023-11-23
Revised Date
2023-12-07
Accepted Date
2023-12-07

Journal of the Korean Society for Information Management

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