What's on your plate? Collecting multimodal data to understand commensal behavior

Area of Science:

• Computational Social Science
• Human-Computer Interaction
• Digital Commensality

Background:

• Eating is a fundamental social activity, yet its digital facilitation remains underexplored.
• Computational Commensality is an emerging field focused on the computational analysis of social eating.
• Understanding remote social dining experiences is crucial in an increasingly connected world.

Purpose of the Study:

• To investigate the phenomenon of Digital Commensality through empirical study.
• To collect and analyze data from remote shared dining experiences.
• To introduce the first Digital Commensality Data-set for future research.

Main Methods:

• Conducted an online study in May 2021 involving 11 pairs of friends sharing a meal remotely via videoconferencing.
• Recorded participants consuming pasta while interacting with a friend or family member.
• Administered the Digital Commensality questionnaire and collected qualitative feedback on technology limitations.

Main Results:

• The study generated a novel dataset comprising videos, facial landmarks, and participant responses.
• Analysis focused on social interactions and the effects of remote commensal experiences.
• Initial findings provide insights into the dynamics of digital shared meals.

Conclusions:

• The study successfully established a foundation for researching Digital Commensality.
• The created dataset offers a valuable resource for investigating commensal behavior computationally.
• Future research can leverage this dataset to explore remote dining and social interaction technologies.