• Title/Summary/Keyword: sejong city library

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Tour Program in Archives: Case Study for the Presidential Archives (기록관의 견학 프로그램 - 대통령기록관을 사례로 -)

  • Lee, Hyewon;Rieh, Hae-young
    • Journal of Korean Society of Archives and Records Management
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    • v.15 no.3
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    • pp.219-245
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    • 2015
  • Archives should promote services to users using various outreach service methods. Although the archives' tour program is one of the effective means of services, there has been few studies on the archival tour program. This study investigated archival tour programs and tried to suggest a desirable tour program, with the Korean Presidential Archives as a case. For this study, four U.S. Presidential Libraries' tour programs were investigated and analyzed. Also, tour programs offered in similar organizations in Korea, such as Kim Daejung Library, Diplomatic Archives of the Ministry of Foreign Affairs, and National Library of Korea, were analyzed. Current tour programs offered by the Korean Presidential Archives were also analyzed and some limitations were identified. Based on the characteristics of the Korean Presidential Archives, which will be moved to independent building in Sejong City soon, desirable direction to organize tour programs for various user groups were suggested.

Understanding Public Opinion by Analyzing Twitter Posts Related to Real Estate Policy (부동산 정책 관련 트위터 게시물 분석을 통한 대중 여론 이해)

  • Kim, Kyuli;Oh, Chanhee;Zhu, Yongjun
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.3
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    • pp.47-72
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    • 2022
  • This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.