The effect of simulated contextual factors on recipe rating and nutritional intake behaviour

Despite the importance of context in Recommender Systems (RSs) more generally, and its clear applicability in the food domain, most existing research focuses on single contextual factors, and only considers simple extrinsic factors such as location and time. No RSs research has systematically explored the impact of multiple dynamic factors, or investigated the effect of emotion in determin-ing people’s eating, recipe rating and nutritional intake behaviour. To bridge these gaps, we conducted a comprehensive large-scale (n=397) crowdsourced experimental study to uncover the intri-cate relationship between various simulated contextual factors and users’ subsequent recipe rating and implied nutritional intake be-haviour. We further aimed to explore how these contextual fac-tors can be incorporated to improve recommendation performance. Four distinct types of contextual factors were investigated: seasonal, emotional, busyness and physical activity, encompassing a total of seven elements. Our findings show that people’s eating prefer-ences and the likelihood of them choosing to eat healthy recipes vary depending on the simulated context they find themselves in. Moreover, we demonstrate how these contextual features can be used to significantly improve recipe rating prediction performance. Our research has implications for the future development of food RSs, and shows that emotion-aware systems could lead to better healthy food recommendations.