Individual and joint body movement assessed by wearable sensing as a predictor of attraction in speed dates

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Abstract

Interpersonal attraction is known to motivate behavioral responses in the person experiencing this subjective phenomenon. Such responses may involve the imitation of behavior, as in mirroring or mimicry of postures or gestures, which have been found to be associated with the desire to be liked by an interlocutor. Speed dating provides a unique opportunity for the study of such behavioral manifestations of interpersonal attraction through the elimination of barriers to initiating communication, while maintaining significant ecological validity. In this paper we investigate the relationship between body movement, measured via accelerometer sensors, and self-reports or ratings of attraction and affiliation in a dataset of 399 speed dates between 72 subjects. Through machine learning experiments, we found that both features derived from a single individual's body movement and features designed to measure aspects of synchrony and convergence of the couple's body movement signals were predictive of different attraction ratings. Our statistical analysis revealed that the overall increase or decrease in an individual's body movement throughout an interaction is a potential indicator of friendly intentions, possibly related to the desire to affiliate.

Original languageEnglish
Number of pages15
JournalIEEE Transactions on Affective Computing
DOIs
Publication statusE-pub ahead of print - 2022

Keywords

  • Accelerometers
  • attraction
  • body movement
  • Convergence
  • convergence
  • Feature extraction
  • Machine learning
  • non-verbal behavior
  • Robot sensing systems
  • Sensors
  • speed dates
  • synchrony
  • Wearable computers

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