Measuring social networks using proximity sensors

Abstract

A significant body of research demonstrates strong connections between social connectedness, stress, and health. However, to date it is unclear whether the beneficial aspects of social connectedness are due to quantity, quality, stability, or role within the network. Here we describe a Bluetooth LE proximity sensor based on the Intel Edison that allows us to track interpersonal distances as function of time while triangulating absolute position. This enables us not only to identify the duration and frequency of social contacts, but also to determine who approaches whom-a feature that is necessary in order to establish social hierarchy structures within the group.