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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

텍스트 마이닝과 토픽모델링 활용한 사회서비스 품질의 학술연구 동향 분석

The Analysis of Research Trends in Social Service Quality Using Text Mining and Topic Modeling

한국사물인터넷학회논문지 / Journal of The Korea Internet of Things Society, (P)2466-0078;
2022, v.8 no.3, pp.29-40
https://doi.org/https://doi.org/10.20465/kiots.2022.8.3.029
이혜정 (남산종합사회복지관)
윤기혁 (동명대학교)
  • 다운로드 수
  • 조회수

초록

본 연구는 텍스트 마이닝과 토픽모델링을 활용하여 우리나라에 사회서비스가 본격적으로 도입된 2007년부터 2020년 까지의 사회서비스 품질에 대한 학술연구 동향을 분석하였다. 이를 토대로 사회서비스 품질에 관한 논문의 패 턴 및 전체 데이터 속에 의미를 파악하여 사회서비스 발전방향에 대한 기초자료를 제공하고자 함에 목적이 있다. 자료 수집은 학술연구정보서비스(RISS)에서 사회서비스, 사회복지서비스, 품질 키워드로 97편의 논문을 선정하였고, 2개 구 간으로 구분하여 텍스트 마이닝을 활용하여 데이터를 분석하였다. 본 연구의 결과는 첫째, 본 연구에서 활용된 97개의 논문 중 1구간은 38편, 2구간은 59편으로 나타났고, 연 평균 6.9개의 논문이 발표되었다. 둘째, 단어빈도 분석 결과 1구간과 2구간의 공통 키워드는 서비스, 품질, 사회서비스, 만족도, 이용자, 품질관리, 재이용, 정책, 바우처 등의 순으 로 나타났다. TF-IDF 분석 결과 1구간과 2구간의 공통 키워드는 사회서비스, 만족도, 이용자, 고객만족, 재이용, 바우 처, 품질, 노인요양시설, 품질관리, 지역사회서비스투자사업 등의 순으로 나타났다. 셋째, 토픽 모델링 분석 결과 1구간 의 주요 토픽은 서비스 제공유형, 서비스 비용, 재이용, 이용자 중심, 일자리 창출로 나타났고, 2구간은 품질관리체계, 공공성, 제공인력 관리체계, 공급방식체계, 서비스 만족도로 나타났다. 본 연구 결과를 바탕으로 사회서비스 품질 학술 연구의 방향성을 제시하였다.

keywords
사회서비스, 사회복지서비스, 품질, 텍스트 마이닝, 토픽모델링, social service, social welfare service, quality, text mining, topic modeling

Abstract

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.

keywords
사회서비스, 사회복지서비스, 품질, 텍스트 마이닝, 토픽모델링, social service, social welfare service, quality, text mining, topic modeling

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