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The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016
The purpose of this study was to investigate the diet tendencies of human and companion animals using big data analysis. The keyword data of human diet and companion animals' diet were collected from the portal site Naver from January 1, 2016 until December 31, 2016 and collected data were anal...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Clinical Nutrition
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665747/ https://www.ncbi.nlm.nih.gov/pubmed/29124046 http://dx.doi.org/10.7762/cnr.2017.6.4.256 |
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author | Jung, Eun-Jin Kim, Young-Suk Choi, Jung-Wa Kang, Hye Won Chang, Un-Jae |
author_facet | Jung, Eun-Jin Kim, Young-Suk Choi, Jung-Wa Kang, Hye Won Chang, Un-Jae |
author_sort | Jung, Eun-Jin |
collection | PubMed |
description | The purpose of this study was to investigate the diet tendencies of human and companion animals using big data analysis. The keyword data of human diet and companion animals' diet were collected from the portal site Naver from January 1, 2016 until December 31, 2016 and collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis and seasonality analysis. In terms of human, the word exercise had the highest frequency through simple frequency analysis, whereas diet menu most frequently appeared in the N-gram analysis. companion animals, the term dog had the highest frequency in simple frequency analysis, whereas diet method was most frequent through N-gram analysis. Keyword network analysis for human indicated 4 groups: diet group, exercise group, commercial diet food group, and commercial diet program group. However, the keyword network analysis for companion animals indicated 3 groups: diet group, exercise group, and professional medical help group. The analysis of seasonality showed that the interest in diet for both human and companion animals increased steadily since February of 2016 and reached its peak in July. In conclusion, diets of human and companion animals showed similar tendencies, particularly having higher preference for dietary control over other methods. The diets of companion animals are determined by the choice of their owners as effective diet method for owners are usually applied to the companion animals. Therefore, it is necessary to have empirical demonstration of whether correlation of obesity between human being and the companion animals exist. |
format | Online Article Text |
id | pubmed-5665747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Korean Society of Clinical Nutrition |
record_format | MEDLINE/PubMed |
spelling | pubmed-56657472017-11-09 The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 Jung, Eun-Jin Kim, Young-Suk Choi, Jung-Wa Kang, Hye Won Chang, Un-Jae Clin Nutr Res Original Article The purpose of this study was to investigate the diet tendencies of human and companion animals using big data analysis. The keyword data of human diet and companion animals' diet were collected from the portal site Naver from January 1, 2016 until December 31, 2016 and collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis and seasonality analysis. In terms of human, the word exercise had the highest frequency through simple frequency analysis, whereas diet menu most frequently appeared in the N-gram analysis. companion animals, the term dog had the highest frequency in simple frequency analysis, whereas diet method was most frequent through N-gram analysis. Keyword network analysis for human indicated 4 groups: diet group, exercise group, commercial diet food group, and commercial diet program group. However, the keyword network analysis for companion animals indicated 3 groups: diet group, exercise group, and professional medical help group. The analysis of seasonality showed that the interest in diet for both human and companion animals increased steadily since February of 2016 and reached its peak in July. In conclusion, diets of human and companion animals showed similar tendencies, particularly having higher preference for dietary control over other methods. The diets of companion animals are determined by the choice of their owners as effective diet method for owners are usually applied to the companion animals. Therefore, it is necessary to have empirical demonstration of whether correlation of obesity between human being and the companion animals exist. Korean Society of Clinical Nutrition 2017-10 2017-10-31 /pmc/articles/PMC5665747/ /pubmed/29124046 http://dx.doi.org/10.7762/cnr.2017.6.4.256 Text en Copyright © 2017. The Korean Society of Clinical Nutrition https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Jung, Eun-Jin Kim, Young-Suk Choi, Jung-Wa Kang, Hye Won Chang, Un-Jae The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title | The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title_full | The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title_fullStr | The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title_full_unstemmed | The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title_short | The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016 |
title_sort | analysis of a diet for the human being and the companion animal using big data in 2016 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665747/ https://www.ncbi.nlm.nih.gov/pubmed/29124046 http://dx.doi.org/10.7762/cnr.2017.6.4.256 |
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