A Keyword Analysis Study on Postpartum Obesity Using Big Data

Hyung-ui Baik, Bo-Kyung Seo, Gyu-Ri Kim and Jung-Eun Ku
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Hyung-ui Baik: Department of Addiction Rehabilitation and Social Welfare, Eulji University, 553 Sanseong-daero, Sujeong-gu, Seongnam-si 13135, Gyeonggi-do, Korea
Bo-Kyung Seo: Department of Addiction Rehabilitation and Social Welfare, Eulji University, 553 Sanseong-daero, Sujeong-gu, Seongnam-si 13135, Gyeonggi-do, Korea
Gyu-Ri Kim: Department of Beauty and Cosmetic Science, Eulji University, 553 Sanseong-daero, Sujeong-gu, Seongnam-si 13135, Gyeonggi-do, Korea
Jung-Eun Ku: Department of Beauty Care, Bucheon University, 25 Sinheung-ro 56 Beon-gil, Wonmi-gu, Bucheon-si 14632, Gyeonggi-do, Korea

IJERPH, 2021, vol. 18, issue 16, 1-8

Abstract: This study selected Google and Naver, the most recognizable Internet portals in Korea, as subjects for analysis. “Postpartum obesity” and “postpartum depression” were used as keywords for data collection. This study aimed to provide basic data for solving maternal problems using big data. Keywords related to postpartum obesity were collected from the portal site Google from 1 January 2019 to 31 December 2019. The collected data were analyzed through simple frequency analysis, N-gram analysis, and keyword network. This study can be used as basic data for postpartum obesity-related programs or academic research. It is also expected to be used for research on the development of a mobile-based customized healthcare system focused on maternal health. Previous papers and data are still insufficient at solving the physical and mental problems related to postpartum obesity and depression. It is necessary to find ways to continuously integrate and collect data from mothers across the country.

Keywords: big data; postpartum obesity; postpartum depression; self-esteem; stress; maternal diet data (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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