@article{ART002835391},
author={Park, Hae-Keung and Youn Ki Hyok},
title={An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2022},
volume={8},
number={2},
pages={41-48},
doi={10.20465/KIOTS.2022.8.2.041}
TY - JOUR
AU - Park, Hae-Keung
AU - Youn Ki Hyok
TI - An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining
JO - Journal of Internet of Things and Convergence
PY - 2022
VL - 8
IS - 2
PB - The Korea Internet of Things Society
SP - 41
EP - 48
SN - 2466-0078
AB - This study tried to empirically explore which issues related to the social service agency for public(as below SSA), that is, social perceptions were formed, by using mess media related to the SSA.
This study is meaningful in that it identifies the overall social perception and trend of SSA through public opinion. In order to extract media trend data, the search used the big data analysis system, Textom, to collect data from the representative portals Naver News and Daum News. The collected texts were 1,299 in 2020 and 1,410 in 2021, for a total of 2,709. As a result of the analysis, first, the most derived words in relation to the frequency of text appearance were 'SSA', 'establishment', and 'operation'. Second, as a result of the N-gram analysis, the pairs of words directly related to the SSA 'SSA and public', 'SSA and opening', 'SSA and launch', and 'SSA and Department Director', 'SSA and Staff', 'SSA and Caregiver' etc. Third, in the results of TF-IDF analysis and word network analysis, similar to the word occurrence frequency and N-gram results, 'establishment', 'operation', 'public', 'launch', 'provided', 'opened', ' 'Holding' and 'Care' were derived. Based on the above analysis results, it was suggested to strengthen the emergency care support group, to commercialize it in detail, and to stabilize jobs.
KW - Text Mining;Public Agency for Social Service;Media Trends;Care;Public
DO - 10.20465/KIOTS.2022.8.2.041
ER -
Park, Hae-Keung and Youn Ki Hyok. (2022). An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining. Journal of Internet of Things and Convergence, 8(2), 41-48.
Park, Hae-Keung and Youn Ki Hyok. 2022, "An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining", Journal of Internet of Things and Convergence, vol.8, no.2 pp.41-48. Available from: doi:10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung, Youn Ki Hyok "An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining" Journal of Internet of Things and Convergence 8.2 pp.41-48 (2022) : 41.
Park, Hae-Keung, Youn Ki Hyok. An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining. 2022; 8(2), 41-48. Available from: doi:10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung and Youn Ki Hyok. "An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining" Journal of Internet of Things and Convergence 8, no.2 (2022) : 41-48.doi: 10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung; Youn Ki Hyok. An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining. Journal of Internet of Things and Convergence, 8(2), 41-48. doi: 10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung; Youn Ki Hyok. An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining. Journal of Internet of Things and Convergence. 2022; 8(2) 41-48. doi: 10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung, Youn Ki Hyok. An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining. 2022; 8(2), 41-48. Available from: doi:10.20465/KIOTS.2022.8.2.041
Park, Hae-Keung and Youn Ki Hyok. "An Analysis on Media Trends in Public Agency for Social Service Applying Text Mining" Journal of Internet of Things and Convergence 8, no.2 (2022) : 41-48.doi: 10.20465/KIOTS.2022.8.2.041
