How Visual Aesthetics and Calorie Density Predict Food Image Popularity on Instagram: A Computer Vision Analysis

Area of Science:

• Digital Nutrition
• Social Media Analysis
• Food Aesthetics

Background:

• Social media platforms like Instagram are primary sources for visual food exposure.
• Understanding factors influencing food image popularity is crucial for public health communication.

Purpose of the Study:

• To identify visual content factors driving food image popularity on Instagram.
• To examine the interplay between visual aesthetics, calorie density, and audience engagement (likes, comments).

Main Methods:

• Collected 53,894 food images from 90 popular food influencers over two years.
• Utilized computer vision techniques to analyze visual aesthetics (color, complexity, repetition) and calorie density.
• Correlated visual features and calorie density with audience engagement metrics.

Main Results:

• Both visual aesthetics and calorie density significantly predicted image popularity.
• Arousing warm colors, feature complexity, and repetition increased engagement; brightness and colorfulness decreased it.
• Higher calorie density positively correlated with likes and comments.
• Visual aesthetic effects were more pronounced for low-calorie images.

Conclusions:

• Visual aesthetics and calorie density are key determinants of food image engagement on social media.
• Tailoring visual elements in health campaigns can enhance persuasive messaging for dietary behaviors.
• The influence of visual cues is context-dependent, varying with food's calorie content.