Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study

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Opis bibliograficzny
Wydane w:	Journal of Medical Internet Research vol. 27 (2025), p. e51638
1. autor:	Li, Chuqin
Kolejni autorzy:	Jordan, Alexis, Ge, Yaorong, Park, Albert
Wydane:	Gunther Eysenbach MD MPH, Associate Professor
Hasła przedmiotowe:	United States > US Risk behavior Long term Healthy food Food consumption Social networks Health status Emotions Popularity COVID-19 Shelter in place Learning Habits Behavior change Change agents Sentiment analysis Social media Obesity Pandemics Neural networks Meals Breakfast Surveillance systems Imagery Behavior modification Surveillance Classification Deep learning Mass media effects Eating behavior Risk assessment Computer mediated communication Data Deaths Changes Rates Mass media images Behavior Health behavior Text analysis Attitudes Viruses Consumption Learning outcomes Mental health Observational studies Diet Risk factors Food
Dostęp online:	Citation/Abstract Full Text + Graphics Full Text - PDF
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