Abstract
Face-to-face interactions are important for a variety of individual behaviors and outcomes. In recent years, a number of human sensor technologies have been proposed to incorporate direct observations in behavioral studies of face-to-face interactions. One of the most promising emerging technologies is the application of active Radio Frequency Identification (RFID) badges. They are increasingly applied in behavioral studies because of their low costs, straightforward applicability, and moderate ethical concerns. However, despite the attention that RFID badges have recently received, there is a lack of systematic tests on how valid RFID badges are in measuring face-to-face interactions. With two studies, we aim to fill this gap. Study 1 (N = 11) compares how data assessed with RFID badges correspond with video data of the same interactions (construct validity) and how this fit can be improved using straightforward data processing strategies. The analyses show that the RFID badges have a sensitivity of 50%, which can be enhanced to 65% when flickering signals with gaps of less than 75 s are interpolated. The specificity is relatively less affected by this interpolation process (before interpolation 97%, after interpolation 94.7%)—resulting in an improved accuracy of the measurement. In Study 2 (N = 73) we show that self-report data of social interactions correspond highly with data gathered with the RFID badges (criterion validity).
Highlights
Face-to-face social interactions are a central activity in human lives and the desire to socialize with others is a core motivation for human behavior (Baumeister & Leary, 1995)
We have shown that the construct validity is reasonable, but not very high: 87.5% of all seconds were identified correctly but about half the actual interaction-seconds were not recorded by the Radio Frequency Identification (RFID) badges
We show that the validity of the RFID badges can be improved, with an accuracy of up to 89.0% and a sensitivity up to 65.6% when the interpolation criterion is used
Summary
Face-to-face social interactions are a central activity in human lives and the desire to socialize with others is a core motivation for human behavior (Baumeister & Leary, 1995). It is important to understand how often, under what circumstances, and with whom individuals engage in such social interactions. Face-to-face interactions have been difficult to measure. 2003), WiFi (Sapiezynski, Stopczynski, Wind, Leskovec, & Lehmann, 2017), or Bluetooth (e.g., Eagle & Pentland, 2006) can help to identify the spatial co-location of individuals and electronic forms of interaction. The resolution of such technologies is too rough to allow identifying when people face each other in a social interaction, as they can capture at most who is in the same room
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