JMIR Publications

ABSTRACT

Background:

Although Pinterest has become a popular platform for distributing influential information that shapes users’ behaviors, the role of recipes pinned on Pinterest has not been well understood.

Objective:

To explore patterns of food ingredients and the nutritional content of recipes posted on Pinterest, and examine the factors associated with recipes that engaged more users.

Methods:

Data were randomly collected from Pinterest between June 28 and July 12, 2020 (207 recipes and 2,818 comments). All samples were collected via two new user accounts with no search history. A codebook was developed with a raw agreement rate of 0.97 across all variables. Content analysis and a novel natural language processing (NLP) sentiment analysis technique were employed.

Results:

Recipes using seafood or vegetables as the main ingredient had on average fewer calories and less sodium, sugar, and cholesterol compared to meat- or poultry-based recipes. For recipes using meat as the main ingredient, more energy was from fat (56.6%). Although the most followed pinners tended to post recipes containing more poultry/seafood and less meat, recipes serving higher fat or providing more calories per serving were more popular, having more shared photos/videos and comments. The NLP-based sentiment analysis suggested that Pinterest users weighted “taste” more heavily than “complexity” (less than 8% of comments) and “health” (less than 3% of comments).

Conclusions:

While popular pinners tended to post recipes with more seafood/poultry/vegetables and less meat, recipes with higher fat and sugar content were more user-engaging, with more photo/video shares and comments. Data on Pinterest behaviors can inform developing and implementing nutrition health interventions on promoting healthy recipes on social media platforms.