ArticleJMIR public health and surveillance2020
YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis.
Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- Perceptions of Sports Betting and Promotions in the U.S.: Evidence from a Mixed-Methods Sentiment Analysis of YouTube Comments.Journal of gambling studies · 2026Article
- Self-Reported Health Outcomes in Metabolic Health YouTube Comments: Cross-Sectional Study and Rule-Based Natural Language Processing Framework Development and Validation.Journal of medical Internet research · 2026Observational
- Digital awareness in spinal cord injury: content and sentiment analysis of the 100 most viewed YouTube videos.Spinal cord · 2026Observational
- Potential link between tastes preference and digestive system cancer hospitalisations in Fujian Province, China: big data analytics.Public health nutrition · 2025Article
- Use of Mukbang in Health Promotion: Scoping Review.Journal of medical Internet research · 2025Article
- From Screen to Plate: How Instagram Cooking Videos Promote Healthy Eating Behaviours in Established Adulthood.Nutrients · 2025Article
- Why am I obsessed with viewing mukbang ASMR? The roles of mediated voyeurism and intertemporal choice.PloS one · 2024Article
- Fifteen years of YouTube scholarly research: knowledge structure, collaborative networks, and trending topics.Multimedia tools and applications · 2023Article
- What to watch: Practical considerations and strategies for using YouTube for research.Digital healthArticle
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPoor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities.
objectiveThe objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters' perceptions and sentiments of healthy eating through text mining techniques.
methodsThis paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.
resultsWith a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.
conclusionsThis study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.