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A Study on the Changes in Perspectives on Unwed Mothers in S.Korea and the Direction of Government Polices: 1995~2020 Social Media Big Data Analysis

한국미혼모에 대한 관점 변화와 정부정책의 방향: 1995년~2020년 소셜미디어 빅데이터 분석

  • Seo, Donghee (Division of Social Welfare, Catholic Kkottongnae University) ;
  • Jun, Boksun (University of South Carolina)
  • Received : 2021.08.17
  • Accepted : 2021.12.20
  • Published : 2021.12.28

Abstract

This study collected and analyzed big data from 1995 to 2020, focusing on the keywords "unwed mother", "single mother," and "single mom" to present appropriate government support policy directions according to changes in perspectives on unwed mothers. Big data collection platform Textom was used to collect data from portal search sites Naver and Daum and refine data. The final refined data were word frequency analysis, TF-IDF analysis, an N-gram analysis provided by Textom. In addition, Network analysis and CONCOR analysis were conducted through the UCINET6 program. As a result of the study, similar words appeared in word frequency analysis and TF-IDF analysis, but they differed by year. In the N-gram analysis, there were similarities in word appearance, but there were many differences in frequency and form of words appearing in series. As a result of CONCOR analysis, it was found that different clusters were formed by year. This study confirms the change in the perspective of unwed mothers through big data analysis, suggests the need for unwed mothers policies for various options for independent women, and policies that embrace pregnancy, childbirth, and parenting without discrimination within the new family form.

본 연구는 1995년부터 2020년까지 기간의 '미혼모', '싱글맘', '비혼모' 키워드를 중심으로 시기별 빅데이터를 수집, 분석하여, 미혼모에 대한 관점 변화에 따른 적절한 정부의 지원정책 방향성을 제시하고자 한다. 자료수집을 위해 빅데이터 수집 플랫폼인 텍스톰을 활용하여 포털검색 사이트 네이버, 다음에서 데이터 수집 후, 데이터를 정제하는 과정을 거쳤다. 최종 정제된 데이터는 텍스톰에서 제공하는 단어빈도분석, TF-IDF 분석, N-gram 분석, UCINET6 프로그램을 통한 Network 분석과 CONCOR 분석을 진행하였다. 연구결과, 단어빈도분석, TF-IDF 분석에서는 유사한 단어들이 출현하였으나 연도별로 차이를 보였고, N-gram 분석에서는 단어 출현의 유사점은 있었으나 빈도수와 연쇄적으로 출현되는 단어들의 형태에 많은 차이가 있었으며 CONCOR 분석결과, 연도별로 다른 군집을 이루는 것을 볼 수 있었다. 본 연구는 미혼모의 관점 변화를 빅데이터의 분석을 통해 확인하고, 독립적인 여성들의 다양한 선택권을 위한 미혼모 정책, 그리고 그에 맞는 차별 없는 임신, 출산, 양육이 새로운 가족의 형태 내로 포용 되는 정책의 필요성을 제언한다.

Keywords

References

  1. My occupational white paper(11) A Mother of 17 siblings (1955. 10. 10). Dong-a Ilbo.
  2. H. J. Kwon. (2019). The Invention of Unwed Mothers: A History of Exiled Mothers in Modern Korea. Incheon:Antonia's.
  3. D. H. Kwak. (1985. 1. 16). Dae-hee Kwak's column<74>, Hymen. Maeil Business Newspaper.
  4. H. H. Jo. (2021. 4. 27). Start of social discussion...; Unmarried family members are also social acknowledgement. MBC. [Online]. https://imnews.imbc.com/news/2021/society/article/6161400_34873.html.
  5. KOSIS. (2021). Population Census. Statistics Korea. [Online] https://kosis.kr
  6. KOSIS (2018). KOSTAT Statistic Plus. Sejong:D.Y.Song.
  7. S. H. Choi. & Y. R. Oh. (2009). Welfare for Women. Paju:Knowledge Community.
  8. Z. I. Yi. (2012). Human Rights of Unwedded Mothers and Legal Policies. Legal Research Institute of Korea University, 64, 139-171.
  9. H. Y. Kim. (2013). Social Exclusion and Discrimination against Unwed Mothers. Gender and Culture, 6(1), 7-14.
  10. S. B. Chae, S. H. Ahn & S. I. Jung. (2012). Big Data: The epicenter of industrial perception fluctuations, CEO Information. 2012. May. 2th. Vol. 851.
  11. H. R. Kim, I. K. Jeon. (2018). Analysis of leisure activity keywords using text mining. Korean Journal of Leisure, Recreation & Park. 42(3), .59-69. https://doi.org/10.26446/kjlrp.2018.9.42.3.59
  12. U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth & R. Uthrusamy. (1996). Advances in knowledge Discovery & Data Mining. AAAI_MIT.
  13. M. Hearst, (1999). Untangling Text Data Mining, in the Proceedings of ACL'99: the 37th Annual Meeting of the Association for Computational Linguistics, University of Maryland, June 20-26.
  14. Y. Lee, S. Kim & K. Y. Park. (2019a), Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of Korea, Korean Economic Review, forthcoming.
  15. J. H. Lee, J. M. Lee & Y. S. Jang. (2017.12.). Analysis of 2018 PyeongChang Olympic keywords using social network big data analysis. Korean Society For Sport Management. 22(6), 73-89. https://doi.org/10.31308/KSSM.22.6.5
  16. M. K. Cha. (2015). Semantic Network Analysis of "Arts management" in Newspaper Articles - From 1990 to 2014. The Journal of Cultural Policy, 9(34), 168-201. DOI : 10.16937/jcp.29.2.201508.168
  17. G. J. Han. (2003). The Meaning and Research Agenda in Network Analysis as Social Science Methodology -based on semantic network analysis-. The Korean Association for the Social Studies Education, 10(2), 219-235.
  18. H. S. Byun & E. H. Jo. (2003). A Study on the Issues of Various Family Appearance and the Direction of Family-Related Acts. Seoul: Korean Women's Development Institute.
  19. Womenlink. (2006. 8. 22). Comment on the Constitutional Court's ruling against the family headship system Constitution. Womenlink. [Online]. https://www.womenlink.or.kr/archives/1216
  20. Ministry for Health, Welfare and Family Affairs. (2009). 2006-2010 1st Plan for Ageing Society and Population. Sejong: Government of the Republic of Korea.
  21. Ministry of Health & Welfare. (2000). 2011-2015 2nd Plan for Ageing Society and Population. Sejong: Government of the Republic of Korea.
  22. Ministry of Health & Welfare, Korea Institute for Health and Social Affairs. (2017). 2016 A Study on the Performance Evaluation of Low Birthrate and Aging Social Policy. Sejong: Ministry of Health & Welfare.