@article{ART003176897},
author={Seunghee Han and Hyewon Lee},
title={An Analysis of News Articles Related to Public Records Using Text Mining},
journal={Journal of Korean Society of Archives and Records Management},
issn={1598-1487},
year={2025},
volume={25},
number={1},
pages={103-127},
doi={10.14404/JKSARM.2025.25.1.103}
TY - JOUR
AU - Seunghee Han
AU - Hyewon Lee
TI - An Analysis of News Articles Related to Public Records Using Text Mining
JO - Journal of Korean Society of Archives and Records Management
PY - 2025
VL - 25
IS - 1
PB - Korean Society of Archives and Records Management
SP - 103
EP - 127
SN - 1598-1487
AB - This study examines the relationship between public records and sociopolitical issues by applying text mining techniques to 5,050 news articles related to public records published from 2000 to 2024. The frequency analysis results indicate that news articles primarily focus on incidents, accidents, and political issues rather than public records, with meeting records being the most frequently mentioned record type. In the Bigram network analysis, the main keywords identified were “dialogue records,” “meeting minutes,” “records,” and “Public Records Management Act.” The network clustering analysis revealed three major themes: (1) public records management, (2) inter-Korean summit meeting records, and (3) controversies surrounding the Public Records Management Act. The sentiment analysis results indicate that positive news articles mainly highlight cases of exemplary record management institutions. Conversely, negative articles focused on Public Records Management Act violations and records management deficiencies. Finally, the study compared research trends with findings from the news article analysis and provided policy recommendations to address and improve social issues related to public records.
KW - Public Records;News Big Data Analysis;Text Mining;Network Cluster Analysis;Sentiment Analysis
DO - 10.14404/JKSARM.2025.25.1.103
ER -
Seunghee Han and Hyewon Lee. (2025). An Analysis of News Articles Related to Public Records Using Text Mining. Journal of Korean Society of Archives and Records Management, 25(1), 103-127.
Seunghee Han and Hyewon Lee. 2025, "An Analysis of News Articles Related to Public Records Using Text Mining", Journal of Korean Society of Archives and Records Management, vol.25, no.1 pp.103-127. Available from: doi:10.14404/JKSARM.2025.25.1.103
Seunghee Han, Hyewon Lee "An Analysis of News Articles Related to Public Records Using Text Mining" Journal of Korean Society of Archives and Records Management 25.1 pp.103-127 (2025) : 103.
Seunghee Han, Hyewon Lee. An Analysis of News Articles Related to Public Records Using Text Mining. 2025; 25(1), 103-127. Available from: doi:10.14404/JKSARM.2025.25.1.103
Seunghee Han and Hyewon Lee. "An Analysis of News Articles Related to Public Records Using Text Mining" Journal of Korean Society of Archives and Records Management 25, no.1 (2025) : 103-127.doi: 10.14404/JKSARM.2025.25.1.103
Seunghee Han; Hyewon Lee. An Analysis of News Articles Related to Public Records Using Text Mining. Journal of Korean Society of Archives and Records Management, 25(1), 103-127. doi: 10.14404/JKSARM.2025.25.1.103
Seunghee Han; Hyewon Lee. An Analysis of News Articles Related to Public Records Using Text Mining. Journal of Korean Society of Archives and Records Management. 2025; 25(1) 103-127. doi: 10.14404/JKSARM.2025.25.1.103
Seunghee Han, Hyewon Lee. An Analysis of News Articles Related to Public Records Using Text Mining. 2025; 25(1), 103-127. Available from: doi:10.14404/JKSARM.2025.25.1.103
Seunghee Han and Hyewon Lee. "An Analysis of News Articles Related to Public Records Using Text Mining" Journal of Korean Society of Archives and Records Management 25, no.1 (2025) : 103-127.doi: 10.14404/JKSARM.2025.25.1.103
