What's on your plate? Collecting multimodal data to understand commensal behavior - Ceccaldi, Eleonora; Niewiadomski, Radoslaw; Mancini, Maurizio; Volpe, Gualtiero (Frontiers in Psychology, 2022)
Eating is a fundamental part of human life and is, more than anything, a social activity. A new field, known as Computational Commensality has been created to computationally address various social aspects of food and eating. Novel data-sets, such as collections of images, videos, motion-capture recordings that focus on food, food consumption, and activities at the table, are needed to develop computational models of human behavior in commensal settings. Here, we review data-sets and corpora that, in such a view, could be exploited to understand commensal behavior. In this, we adopt a multimodal approach, considering audio, video, motion capture, and image data-sets. After surveying existing data-sets, we discuss methodological and theoretical issues behind studying commensality through data-sets. Furthermore, following this idea of leveraging data-sets to investigate commensal scenarios, we illustrate a study on remote dining we conducted online during May 2021. To have a better understanding of this phenomenon, known as Digital Commensality we recorded 11 pairs of friends sharing a meal online through a videoconferencing app. In the videos, participants consume a plate of pasta while chatting with a friend or a family member. After the remote dinner, participants were asked to fill in the Digital Commensality questionnaire, a validated questionnaire assessing the effects of sharing a meal on social interaction. Here, we comment on the feasibility of using remote meals as a source to build data-sets to investigate commensal behavior and explore possible future research directions emerging from our results.