Social Interaction Data-sets in the Age of Covid-19: a Case Study on Digital Commensality

Abstract

Research focusing on social interaction often leverages data-sets, allowing annotation, analysis, and modeling of social behavior. When it comes to commensality, researchers have started working on computational models of food and eating-related activities recognition. The growing research area known as Digital Commensality, has focused on meals shared online, for instance, through videochat. However, to investigate this topic, traditional data-sets recorded in laboratory settings may not be the best option in terms of ecological validity. Covid-19 restrictions and lock-downs have increased in online gatherings, with many people becoming used to the idea of sharing meals online. Following this trend, we propose the concept of collecting data by recording online interactions and discuss the challenges related to this methodology. We illustrate our approach in creating the first Digital Commensality data-set, containing recordings of food-related social interactions collected online during the Covid-19 outbreak.

Social robots as eating companions

“…), is another open challenge. The first datasets (Ceccaldi et al, 2022) and computational models detecting, e.g., chewing and speaking in a video data were only recently proposed (Hossain et al, 2020;Rouast and Adam, 2020). Such models are, however, indispensable to building human-robot verbal interaction in the commensal setting.…”