DOI QR코드

DOI QR Code

Analysis of preference convergence by analyzing search words for oralcare products : Using the Google trend

구강관리용품에 대한 검색어 분석을 통한 선호도 융합 분석 : 구글트렌드를 이용하여

  • Moon, Kyung-Hui (Department of Dental Hygiene, Jinju Health College) ;
  • Kim, Jang-Mi (Department of Oral Health Graduate School of Public Health & Social Welfare Dankook University)
  • 문경희 (진주보건대학교 치위생과) ;
  • 김장미 (단국대학교 보건복지대학원 구강보건학과)
  • Received : 2019.03.15
  • Accepted : 2019.06.20
  • Published : 2019.06.28

Abstract

This study used the Google Trends site to analyze selection information that users expect from prominent Toothbrushes and Toothpastes through related search keywords that users wanted to obtain. From 2006 to 2018(sep), searches for Toothbrushes and Toothpastes were arranged in the order of popularity of related searched words. The total number of searches words exposed was each 25, total 325 collected. The analysis was conducted using two methods, first, by search function. second, by a word network using a Big Data program. The study has shown that toothbrushes there are high expectations for brands, toothpaste there are high expectations in the function. In order to increase the motivation for oral health education, it is recommended to use and provide knowledge about the brand of toothbrushes and Toothpastes by the function.

본 연구는 구강관리용품 중 가장 대표적인 칫솔과 치약에서 이용자가 얻고자 하는 관련검색어를 통하여 이용자가 기대하는 선택정보를 구글 트렌드를 활용, 분석하여 이를 구강관리용품에 대한 교육의 기초자료로 제공하고자 한다. 구글 트렌드에서 제공하는 최초 시점인 2006년부터 2018년 현재(9월)까지의 시기에서 영문 Toothbrush와 Toothpaste를 검색한 뒤 인기순으로 정렬하여 노출되는 관련 검색어 각 25개 총325개의 검색어를 연도별로 수집하였다. 그 후 이용자가 기대하는 검색기능을 파악하는 검색어 세부분석방법과 빅데이터 프로그램 넷마이너를 활용한 단어 네트워크 분석의 두가지 방법으로 분석하였다. 연구 결과 전 세계적으로 Toothbrush에 대하여 브랜드에 대한 기대와 관심이 높았으며 Toothpaste에 대하여 치약의 기능에 대한 기대와 관심이 높았다. 이를 통해 구강교육의 동기부여를 높이기 위해 칫솔은 브랜드, 치약은 치약의 기능에 대한 지식과 정보를 활용하고 제공함으로써 환자의 흥미를 높이는 것이 효과적으로 판단된다.

Keywords

OHHGBW_2019_v10n6_59_f0001.png 이미지

Fig. 1. Result of compare between keywords

Table 1. Result of the toothbrush keyword analysis

OHHGBW_2019_v10n6_59_t0001.png 이미지

Table 2. Result of the toothpaste keyword analysis

OHHGBW_2019_v10n6_59_t0002.png 이미지

Table 3. Result of the toothbrush network analysis

OHHGBW_2019_v10n6_59_t0003.png 이미지

Table 4. Result of the toothpaste network analysis

OHHGBW_2019_v10n6_59_t0004.png 이미지

References

  1. J. B. Kim, H. S. Moon, D. I. Paik & Y. H. Lee. (2000). 'A survey on family dental health behavior in Seoul capital city'. THE JOURNAL OF THE KOREAN ACADEMY OF DENTAL HEALTH, 24(3), 239-254.
  2. H. Y. Moon. (2009). A Study on Labelling and Advertising System of Oral Care Products. Korean Journal of Local Government & Administration Studies, 23(2), 445-463.
  3. H. K. Kwon. (2006). Primary preventive dentistry. Daehan Nare Publishing Company.
  4. Naver Knowledgeback. https://terms.naver.com/entry.nhn?cid=59931&docId=4369087&categoryId=59931.
  5. J. Y. Lee, J. H. Lee & Y. H. Park. (2016). A design and implementation of the management system for number of keyword searching results using Google searching engine. Journal of information and communication convergence engineering, 20(5), 880-886.
  6. Ecommerce platforms. (2018). What is GoogleTrends?. https://ecommerce-platforms.com/glossary/google-tr ends.
  7. A. Al-Imam. (2017). Google Trends Analyses and Case Report: A Persistently Dilated Pupil in Psychedelics' User. Global Journal of Health Science, 2017, 9(11), 168. https://doi.org/10.5539/gjhs.v9n11p168
  8. J. I. Oh. (2017). Global hot issue big data. The Korean journal of bigdata, 2(1), 1-3. https://doi.org/10.36498/kbigdt.2017.2.2.1
  9. H. R. Choi, S. W. Lee, Y. A. Kim, J. H. Lee, H. Go & H. C. Kim (2017). The Necessity and Case Analysis of Bigdata Quality Control in Medical Institution, The Korean journal of bigdata, 2(1), 67-74. https://doi.org/10.36498/kbigdt.2017.2.2.67
  10. S. S. Lee. (2013). Analytical Study on the Relationship between Centralities of Research Networks and Research Performances. Journal of Korean Library and Information Science Society, 44(3), 405-428. https://doi.org/10.16981/kliss.44.3.201309.405
  11. Wikipedia (2018). Netminer search result. https://ko.wikipedia.org/w/index.php?title=%EB%84%B7%EB%A7%88%EC%9D%B4%EB%84%88&oldid=22318449.
  12. L. C. Freeman. (1979). Centrality in social networks conceptual clarification, Social Networks, 1(3), 215-239. https://doi.org/10.1016/0378-8733(78)90021-7
  13. T. M. Song. (2012). Multivariate Analysis of Suicide Causes Using Big Data. Health and Welfare Issue&Focus, 168, 1-8.
  14. J. H. Kim, H. Kim, G. E. Sohn, Y. S. Song, J. H. Yoon, H. C. Lim & S. H. Jung. (2014). Communications of the Korean Institute of Information Scientists and Engineer, 32(3), 18-26.
  15. D. I. Baek. (2012). Clinical preventive dentistry. Seoul. KMS.