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@article{ART002855194},
author={Hae-Jung Lee and Youn Ki Hyok},
title={The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2022},
volume={8},
number={3},
pages={29-40},
doi={10.20465/KIOTS.2022.8.3.029}

TY - JOUR
AU - Hae-Jung Lee
AU - Youn Ki Hyok
TI - The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling
JO - Journal of Internet of Things and Convergence
PY - 2022
VL - 8
IS - 3
PB - The Korea Internet of Things Society
SP - 29
EP - 40
SN - 2466-0078
AB - The aim of this study was to analyze research trends of social service quality from 2007 to 2020 based on text mining and topic modeling. Our focus was to provide foundational materials for social service improvement by discovering the latent meaning of relevant research papers. We collected 97 scholarly articles on social service, social welfare service, and quality from RISS, and implemented two segments of text mining analysis. Our results showed that the first section included 38 papers and the second 59, indicating 6.9 articles annually. Word frequency results demonstrated that the common keywords of both sections were ‘service’, ‘quality’, ‘social service’, ‘satisfaction’, ‘users’, ‘quality control’, ‘reuse’, ‘policy’, ‘voucher’, etc. TF-IDF suggested that ‘social service’, ‘satisfaction’, ‘users’, ‘customer satisfaction', ‘revisiting’, ‘voucher’, ‘quality’, ‘assisted living facility’, ‘quality control’, ‘community service investment business’, etc., were represented in both categories. Lastly, topic modeling analysis revealed that the first segment displayed ‘types of care services’, ‘service costs’, ‘reuse’, ‘users based’, and ‘job creation’, whereas the second presented ‘service quality’, ‘public value’, ‘management system of human resources’, ‘service provision system’, and ‘service satisfaction’. Future directions of social service quality were discussed based on the results.
KW - social service;social welfare service;quality;text mining;topic modeling
DO - 10.20465/KIOTS.2022.8.3.029
ER -

Hae-Jung Lee and Youn Ki Hyok. (2022). The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling. Journal of Internet of Things and Convergence, 8(3), 29-40.

Hae-Jung Lee and Youn Ki Hyok. 2022, "The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling", Journal of Internet of Things and Convergence, vol.8, no.3 pp.29-40. Available from: doi:10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee, Youn Ki Hyok "The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling" Journal of Internet of Things and Convergence 8.3 pp.29-40 (2022) : 29.

Hae-Jung Lee, Youn Ki Hyok. The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling. 2022; 8(3), 29-40. Available from: doi:10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee and Youn Ki Hyok. "The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling" Journal of Internet of Things and Convergence 8, no.3 (2022) : 29-40.doi: 10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee; Youn Ki Hyok. The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling. Journal of Internet of Things and Convergence, 8(3), 29-40. doi: 10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee; Youn Ki Hyok. The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling. Journal of Internet of Things and Convergence. 2022; 8(3) 29-40. doi: 10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee, Youn Ki Hyok. The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling. 2022; 8(3), 29-40. Available from: doi:10.20465/KIOTS.2022.8.3.029

Hae-Jung Lee and Youn Ki Hyok. "The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling" Journal of Internet of Things and Convergence 8, no.3 (2022) : 29-40.doi: 10.20465/KIOTS.2022.8.3.029