TY - JOUR
T1 - Individual and Joint Body Movement Assessed by Wearable Sensing as a Predictor of Attraction in Speed Dates
AU - Vargas-Quiros, Jose
AU - Kapcak, Oyku
AU - Hung, Hayley
AU - Cabrera-Quiros, Laura
N1 - Publisher Copyright:
© 2010-2012 IEEE.
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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.
AB - 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.
KW - Attraction
KW - body movement
KW - convergence
KW - non-verbal behavior
KW - speed dates
KW - synchrony
UR - http://www.scopus.com/inward/record.url?scp=85122102086&partnerID=8YFLogxK
U2 - 10.1109/TAFFC.2021.3138349
DO - 10.1109/TAFFC.2021.3138349
M3 - Artículo
AN - SCOPUS:85122102086
SN - 1949-3045
VL - 14
SP - 2168
EP - 2181
JO - IEEE Transactions on Affective Computing
JF - IEEE Transactions on Affective Computing
IS - 3
ER -