JMIR Publications

ABSTRACT

Background:

Poor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover the reasons behind and patterns of food choices, in addition to exploring the sentiments of healthy eating in networked communities.

Objective:

The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviours in online communities, and to provide insight into YouTube video commenters’ perceptions and sentiments of healthy eating through text mining technique.

Methods:

This paper applied the text mining technique to identify and categorise 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 modelling procedure.

Results:

With a large dataset of 4,654 comments extracted from YouTube videos in the context of Malaysia, we apply the text mining method to analyse the perceptions and behaviour of healthy eating. There were ten clusters identified with regards to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The SEM 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 favourable perception of healthy eating, people may not purchase commonly recognised healthy food if it has a premium price. Weight concerns are what people associate healthy eating with. Food taste, variety, and availability are identified as the reasons why Malaysians cannot act on eating healthily.

Conclusions:

This 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 modelling techniques to identify thematic constructs and to analyse the sentiments of healthy eating.