Reddit study: XGBoost predicts food post engagement from calorie density

A new paper from Gabriela Ozegovic, Thorsten Ruprechter, and Denis Helic (arXiv:2502.07377) tackles a timely question: what drives engagement with food content on social media? Unlike prior work focused on visual appeal, this study digs into nutritional data. The team scraped nearly half a million food posts from Reddit, extracting calorie and macronutrient information using automated tools. They then trained a series of XGBoost models – a popular gradient-boosting framework – to predict the number of comments each post received.

The results confirm a disheartening trend for nutrition advocates: calorie density emerged as the single most predictive nutritional feature, with higher-calorie meals consistently driving more comments. Posts featuring nutrient-dense, high-calorie foods like burgers, pizza, and pasta outperformed low-calorie alternatives by a wide margin. Incorporating nutritional features improved the model's baseline accuracy by almost 5%, suggesting that what a meal contains matters almost as much as how it looks when predicting viral potential. The authors suggest these insights could help design more engaging health campaigns by, for example, presenting healthy dishes that still feel indulgent.