Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool
We explored online search interest in dieting and weight loss using big-data analysis with a view to its potential utility in global obesity prevention efforts. We applied big-data analysis to the global dieting trends collected from Google and Naver search engines from January 2004 to January 2018...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
|
| Series: | Nutrients |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6643/13/4/1069 |
| _version_ | 1797540039315423232 |
|---|---|
| author | Myung-Bae Park Ju Mee Wang Bernard E. Bulwer |
| author_facet | Myung-Bae Park Ju Mee Wang Bernard E. Bulwer |
| author_sort | Myung-Bae Park |
| collection | DOAJ |
| description | We explored online search interest in dieting and weight loss using big-data analysis with a view to its potential utility in global obesity prevention efforts. We applied big-data analysis to the global dieting trends collected from Google and Naver search engines from January 2004 to January 2018 using the search term “diet,” in selected six Northern and Southern Hemisphere countries; five Arab and Muslim countries grouped as conservative, semi-conservative, and liberal; and South Korea. Using cosinor analysis to evaluate the periodic flow of time series data, there was seasonality for global search interest in dieting and weight loss (amplitude = 6.94, CI = 5.33~8.56, <i>p</i> < 0.000) with highest in January and the lowest in December for both Northern and Southern Hemisphere countries. Seasonal dieting trend in the Arab and Muslim countries was present, but less remarkable (monthly seasonal seasonality, amplitude = 4.07, CI = 2.20~5.95, <i>p</i> < 0.000). For South Korea, seasonality was noted on Naver (amplitude = 11.84, CI = 7.62~16.05, <i>p</i> < 0.000). Our findings suggest that big-data analysis of social media can be an adjunct in tackling important public health issues like dieting, weight loss, obesity, and food fads, including the optimal timing of interventions. |
| first_indexed | 2024-03-10T12:54:24Z |
| format | Article |
| id | doaj.art-9b022fd5fa194354bace7390faa85b6a |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-10T12:54:24Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nutrients |
| spelling | doaj.art-9b022fd5fa194354bace7390faa85b6a2023-11-21T12:00:47ZengMDPI AGNutrients2072-66432021-03-01134106910.3390/nu13041069Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful ToolMyung-Bae Park0Ju Mee Wang1Bernard E. Bulwer2Department of Gerontal Health and Welfare, Pai Chai University, Daejeon 35345, KoreaDepartment of Gerontal Health and Welfare, Pai Chai University, Daejeon 35345, KoreaThe Korean Cardiac Research Foundation, Seoul 04158, KoreaWe explored online search interest in dieting and weight loss using big-data analysis with a view to its potential utility in global obesity prevention efforts. We applied big-data analysis to the global dieting trends collected from Google and Naver search engines from January 2004 to January 2018 using the search term “diet,” in selected six Northern and Southern Hemisphere countries; five Arab and Muslim countries grouped as conservative, semi-conservative, and liberal; and South Korea. Using cosinor analysis to evaluate the periodic flow of time series data, there was seasonality for global search interest in dieting and weight loss (amplitude = 6.94, CI = 5.33~8.56, <i>p</i> < 0.000) with highest in January and the lowest in December for both Northern and Southern Hemisphere countries. Seasonal dieting trend in the Arab and Muslim countries was present, but less remarkable (monthly seasonal seasonality, amplitude = 4.07, CI = 2.20~5.95, <i>p</i> < 0.000). For South Korea, seasonality was noted on Naver (amplitude = 11.84, CI = 7.62~16.05, <i>p</i> < 0.000). Our findings suggest that big-data analysis of social media can be an adjunct in tackling important public health issues like dieting, weight loss, obesity, and food fads, including the optimal timing of interventions.https://www.mdpi.com/2072-6643/13/4/1069big-datadietweight lossgoogleseasonalitycosinor |
| spellingShingle | Myung-Bae Park Ju Mee Wang Bernard E. Bulwer Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool Nutrients big-data diet weight loss seasonality cosinor |
| title | Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool |
| title_full | Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool |
| title_fullStr | Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool |
| title_full_unstemmed | Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool |
| title_short | Global Dieting Trends and Seasonality: Social Big-Data Analysis May Be a Useful Tool |
| title_sort | global dieting trends and seasonality social big data analysis may be a useful tool |
| topic | big-data diet weight loss seasonality cosinor |
| url | https://www.mdpi.com/2072-6643/13/4/1069 |
| work_keys_str_mv | AT myungbaepark globaldietingtrendsandseasonalitysocialbigdataanalysismaybeausefultool AT jumeewang globaldietingtrendsandseasonalitysocialbigdataanalysismaybeausefultool AT bernardebulwer globaldietingtrendsandseasonalitysocialbigdataanalysismaybeausefultool |