A Study on Social Perceptions of Public Libraries Utilizing the sentiment analysis
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This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, ‘Library’ and ‘Lifelong Learning Center’ from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, ‘reading’ and ‘book’ were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.
Abstract
This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, ‘Library’ and ‘Lifelong Learning Center’ from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, ‘reading’ and ‘book’ were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.
참고문헌 (11)
- Choi, S., "Network analysis for communication research" (2016), Communication Books
- 장덕현, "부산지역 공공도서관에 대한 이용자 인식과 요구 분석", 한국문헌정보학회지, 54(1), pp.51~70 (2020), 한국문헌정보학회
- 함유진, "대학도서관에서의 색채이미지와 감성평가 연구 - H대학교 도서관의 현황조사를 중심으로 -", 한국실내디자인학회 논문집, 24(5), pp.42~50 (2015), 한국실내디자인학회
- 김선애, "구립 공공도서관에 대한 지역주민의 인식 및 요구에 관한 연구 - 마포 구립도서관 이용자를 대상으로 -", 한국문헌정보학회지, 54(2), pp.29~52 (2020), 한국문헌정보학회
- Lee, S. S., "Network analysis methods" (2012), Nonhyungbook
- 이종화, "TF-IDF를 활용한 한글 자연어 처리 연구", 정보시스템연구, 28(3), pp.105~121 (2019), 한국정보시스템학회
- 노동조, "대학도서관 공간 평가를 위한 감성어휘 도출에 관한 연구", 한국비블리아학회지, 26(4), pp.83~104 (2015), 한국비블리아학회[DOI]
- 노영희, "도서관 복합문화공간에 대한 이용자 인식 연구", 한국문헌정보학회지, 53(4), pp.23~50 (2019), 한국문헌정보학회
- 표순희, "공공도서관에 대한 사서와 이용자 인식 비교 연구- 서울시교육청 소속 공공도서관을 대상으로 -", 한국문헌정보학회지, 52(2), pp.221~244 (2018), 한국문헌정보학회[DOI]
- Yim, D., "Big data analysis using R" (2015), Jayuacademy
- Yu, Y, "Analysis of media coverage on 2015 revised curriculum policy using big data analysis", doctor, pp.2015
