Are Food Ingredient Social? An Empirical Investigation

Understanding the structural organization of ingredient relationships within cuisines can reveal fundamental patterns in culinary traditions and ingredient co-occurrence. In this paper, we constructed ingredient networks (InNs) from two datasets of recipe ingredients that include recipes from 10 cuisines around the world. We then performed an empirical investigation of these multicuisine InNs to examine their structural characteristics. Our analysis demonstrates that networks exhibit scale-free behavior, with degree distributions following a power law characterized by exponents ranging from γ = 1.96 to γ = 2.38 . This further aligns with statistical validation, where the R -squared values range from 0.9965 to 0.9991, and the p -values are extremely low ( 10 − 25 to 10 − 30 ), reinforcing the robustness of the power law fit. Additionally, the networks display ultra-small-world properties, as evidenced by their short network diameter of approximately 4. These structural measurements highlight striking similarities between InNs and widely studied social networks, suggesting underlying patterns reflective of social-like dynamics. Furthermore, the communities formed within these InNs show a strong correlation with the categorical grouping of recipes, providing insights into the evolution of culinary traditions and ingredient compatibility.