• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Analysis of Infertility Keywords in the Largest Domestic Mom Cafe Bulletin Board in Korea Using Text Mining


Sangmin Lee, Journal of Internet Computing and Services, Vol. 24, No. 4, pp. 137-144, Aug. 2023
10.7472/jksii.2023.24.4.137, Full Text:
Keywords: Infertility, sterility, infertility policy, infertility stress, infertility quality of life

Abstract

The purpose of this study is to examine consumers' perceptions of domestic infertility support policies based on infertility-related keywords and the trends of their changes. To this end, Momsholic, a mom cafe which has the most active infertility-related bulletin boards on Naver, was selected as the analysis target, and 'infertility' was selected as a keyword for data search. The data was collected for three months. In addition, network analysis and visualization were performed using R for data collection and analysis, and cross-validation was attempted using the NetDraw function of 'textom 1.0' and the UCINET6 program. As a result of the analysis, the main keywords were cost, artificial insemination, in vitro fertilization, freezing, harvest, ovulation, and how much. Next, looking at the central value of the degree of connection, it was found that the degree of connection between the words cost, cost, how much, problem, public health center, and artificial insemination was high. According to the results of this study, women who visit mom cafes due to infertility in Korea are more interested in the cost. It is believed to be closely related to infertility treatment as well as in vitro fertilization and egg freezing. Therefore, by examining keywords related toinfertility, it has academic significance in that it is possible to identify major factors that end users are interested in. Furthermore, it is possible to redefine the guidelines for domestic infertility support policies by presenting infertility support policies that reflect the factors of interest of end consumers.


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Cite this article
[APA Style]
Lee, S. (2023). Analysis of Infertility Keywords in the Largest Domestic Mom Cafe Bulletin Board in Korea Using Text Mining. Journal of Internet Computing and Services, 24(4), 137-144. DOI: 10.7472/jksii.2023.24.4.137.

[IEEE Style]
S. Lee, "Analysis of Infertility Keywords in the Largest Domestic Mom Cafe Bulletin Board in Korea Using Text Mining," Journal of Internet Computing and Services, vol. 24, no. 4, pp. 137-144, 2023. DOI: 10.7472/jksii.2023.24.4.137.

[ACM Style]
Sangmin Lee. 2023. Analysis of Infertility Keywords in the Largest Domestic Mom Cafe Bulletin Board in Korea Using Text Mining. Journal of Internet Computing and Services, 24, 4, (2023), 137-144. DOI: 10.7472/jksii.2023.24.4.137.