Journal of the Korean Society for information Management (정보관리학회지)

Korean Society for Information Management (한국정보관리학회)
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An Analysis of News Report Characteristics on Archives & Records Management for the Press in Korea: Based on 1999~2018 News Big Data

뉴스 빅데이터를 이용한 우리나라 언론의 기록관리 분야 보도 특성 분석: 1999~2018 뉴스를 중심으로

  • 한승희 (서울여자대학교 사회과학대학 문헌정보학과)
  • Received : 2018.08.18
  • Accepted : 2018.09.19
  • Published : 2018.09.30
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Abstract

The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

이 연구에서는 1999년 1월부터 2018년 6월 현재까지 약 20년 간의 기록관리를 주제로 한 뉴스 빅데이터 4,680 건을 '빅카인즈'에서 추출하여, 이를 대상으로 우리나라 언론의 기록관리 주제에 대해 시계열 기반으로 보도 특성을 분석하고자 하였다. 먼저, 기록관리에 대한 언론 보도량의 차이를 살펴보기 위해 시기별, 주제별, 언론사 유형별 보도량을 분석하였다. 또한 기록관리 주제에 대한 언론 보도 내용의 차이에 대한 특성을 분석하기 위해 단어빈도 기반 내용 분석과 언어 네트워크 분석을 수행하여 언론 보도 내용의 시기별, 주제별, 언론사 유형별 차이를 분석하였다. 분석 결과, 기록관리 분야 뉴스 보도는 보도량과 보도 내용에 있어 시기별, 주제별, 언론사별로 차이가 있는 것으로 나타났다. 뉴스 보도량은 2007년 대통령기록물관리법이 제정된 이후부터 증가하기 시작하여 2013년에 가장 많은 뉴스가 보도된 것으로 나타났으며, 정치와 사회 주제를 중심으로 중앙지와 경제지가 가장 많은 양의 뉴스를 보도한 것으로 나타났다. 또한 뉴스 보도 내용의 분석결과, 기록관리가 도입된 처음 10년 동안은 기록관리의 현장 적용과 확산 과정에서 발생하는 이슈들을 중심으로 뉴스 주제가 형성되다가, 대통령기록물관리법 제정 이후로 기록관리가 정치적, 사회적 이슈의 주요 요인이 되면서 정치, 사회분야의 뉴스가 많이 보도된 것으로 나타났다.

Keywords

Acknowledgement

Supported by : 서울여자대학교

References

  1. Kang, Beomil, Song, Min, & Jho, Whasun (2013). A study on opinion mining of newspaper texts based on topic modeling. Journal of the Korean Society for Library and Information Science, 47(4), 315-334. http://dx.doi.org/10.4275/KSLIS.2013.47.4315
  2. National Science Museum of Korea (2018, June 1). What is the big data? Retrieved from https://smart.science.go.kr/scienceSubject/bigdata/view.action?menuCd=DOM_000000101001013000&subject_sid=1201
  3. Kim, Bong Je (2018). A study on the characteristics of the use of moral and ethical terms in korean society through big data analysis. Journal of Moral & Ethics Education, (58), 27-58.
  4. Kim, Soo-Yeon, Kim, Daewook, & Choi, Myung-Il (2013). Semantic network analysis of advertising and public relations studies in korea - Using key words in Advertising Research, The Korean Journal of Advertising, The Journal of Public Relations Research, and The Korean Journal of Advertising and Public Relation, The Korean Journal of Advertising and Public Relations, 15(1), 59-85.
  5. Kim, Hee-Jung (2006). A study on the serial analysis and expansion of research areas of records management and archives. Journal of Korean Society of Archives and Records Management, 6(2), 5-25.
  6. Park, Daemin (2013). News information source network analysis as a big data analysis method of news articles. Korean Journal of Journalism & Communication Studies, 57(6), 234-262.
  7. Park, Daemin (2016). Automated time series content analysis with news big data analytics: Analyzing sources and quotes in one million news articles for 26 years. Korean Journal of Journalism & Communication Studies, 60(5), 353-407. https://doi.org/10.20879/kjjcs.2016.60.5.013
  8. Park, Seung Jeong, John, Jino, Kim, Seon Woo, & Kim, Sung Tae (2017). A big-data analysis of presidential issue ownership of two prestigious korean newspapers: Focusing on LDA (latent dirichlet allocation) topic modeling. The Journal of Political Science & Communication, 20(3), 25-55. http://dx.doi.org/10.15617/psc.2017.10.31.3.25
  9. Park, JunHyeong, Ryu, Pum-Mo, & Oh, Hyo-Jung (2018). Timeline-based topic trend analysis of archives management in Korea. Journal of Korean Society of Archives and Records Management, 18(1), 29-47. http://dx.doi.org/10.14404/JKSARM.2018.18.1.029
  10. Park, Han Woo, & Leydesdorff, L. (2004). Understanding the KrKwic: A computer program for the analysis of Korean text. Journal of the Korean Data Analysis Society, 6(5), 1377-1388.
  11. Seo, Eun-Gyoung, & Yu, So-Young (2013). Detecting research trends in Korean information science research, 2000-2011. Journal of the Korean Society for Information Management, 30(4), 215-239. http://dx.doi.org/10.3743/KOSIM.2013.30.4.215
  12. Sung, Ji-Young, & Kim, Sung-Kyun (2017). Interpretation of the place discourse of Deoksugung Doldam-gil through news big data. Journal of Digital Contents Society, 18(5), 923-932. http://dx.doi.org/10.9728/dcs.2017.18.5.923
  13. Shin, Seongheon (2016, Aug, 10). [Media innovator] "Bigkinds, analyzing 30 million news articles... 2 years ahead of IBM." Chosun Biz. Retrieved from http://biz.chosun.com/site/data/html_dir/2016/08/10/2016081001399.html
  14. Yoo, Sarah (2010). A diagnostic analysis of metadata R&D status in Korea. Journal of the Korean Society for Library and Information Science, 44(2), 405-426. http://dx.doi.org/10.4275/KSLIS.2010.44.2.405
  15. Lee, Soo-Sang (2012). Network analysis methods. Seoul: Nonhyung.
  16. Lee, Soo-Sang (2017). Analysis of social issues of the newspaper articles on Gyeongju earthquakes. Journal of the Korean Library and Information Science Society, 48(2), 53-72. http://dx.doi.org/10.16981/kliss.48.201706.53
  17. Lee, Eunbyul, John, Jino, & Baek, Jeesun (2017). A study of multicultural space in Seoul: Analysing the coverage of foreign communities with news big data analytics 'BigKinds' for 27 years. Journal of Media Economics & Culture, 15(2), 7-43. http://dx.doi.org/10.21328/JMEC.2017.5.15.2.7
  18. Lee, Jae-Yun, Moon, Ju-Young, & Kim, Hee-Jung (2007). Examining the intellectual structure of records management & archival science in Korea with text mining. Journal of the Korean Society for Library and Information Science, 41(1), 345-372. https://doi.org/10.4275/KSLIS.2007.41.1.345
  19. Jang, Jeong-Woo, & Choi, Kyoung-Ho (2012). Statistics act content analysis using semantic network analysis. Journal of Korean Official Statistics, 17(2), 53-66.
  20. Choi, Yoon-jung, & Kweon, Sang-Hee (2014). A semantic network analysis of the newspaper articles on big data. Journal of Cybercommunication Academic Society, 31(1), 241-286.
  21. Choi, Hyung Wook, Choi, Ye-Jin, & Nam, So-Yeon (2018). Time series analysis of intellectual structure and research trend changes in the field of library and information science: 2003 to 2017. Journal of the Korean Society for Information Management, 35(2), 89-114. http://dx.doi.org/10.3743/KOSIM.2018.35.2.089
  22. Kakao Corp. (2015). Daum Kakao, providing Daum news layout and key data on the official blog. Kakao Press Release. Retrieved from https://www.kakaocorp.com/kakao/prChannel/pressReleasesView?boardIdx=8356¤tPage=1¤tGroup=1
  23. Korea Press Foundation (2018). Bigkinds user manual. Retrieved from https://www.kinds.or.kr/manual/%EB%B9%85%EC%B9%B4%EC%9D%B8%EC%A6%88_%EC%82%AC%EC%9A%A9%EC%9E%90%EB%A7%A4%EB%89%B4%EC%96%BC.pdf
  24. Blei, D. M. (2012). Probabilistic topic modeling, Communications of the ACM, 55(4), 77-84. http://dx.doi.org/10.1145/2133806.2133826
  25. Borgatti, S. P. (2002). NetDraw: graph visualization software. Harvard: Analytic Technologies.
  26. Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). Ucinet 6 for Windows: software for social network analysis. Harvard, MA: Analytic Technologies.