Automated Methods to Examine Nonverbal Synchrony in Dyads

Norah E. Dunbar, Judee K. Burgoon, Ken Fujiwara
Understanding Social Behavior in Dyadic and Small Group Interactions, PMLR 173:204-217, 2022.

Abstract

Interpersonal synchrony is when two parties in an interaction engage similarly due to the rhythmic coordination of their behavioral patterns. The study of synchrony in communication and psychology dates back to the 1960s but has evolved over time. Historically, studying synchrony has involved the manual coding of nonverbal cues by trained human coders, such as counting the occurrence of a specific behavior or making subjective ratings about a speaker. However, its time-consuming nature has been a serious barrier to the development of the field and has made it difficult for new scholars to adopt the technique. Recent advances in automated coding techniques allow researchers to collect nonverbal behavioral data effectively and objectively, and in a much more efficient manner than laborious manual coding methods historically relied upon. This chapter will review some of the theoretical and methodological challenges in studying interpersonal synchrony and propose alternatives using automated computer vision techniques.

Cite this Paper

BibTeX
@InProceedings{pmlr-v173-dunbar22a, title = {Automated Methods to Examine Nonverbal Synchrony in Dyads}, author = {Dunbar, Norah E. and Burgoon, Judee K. and Fujiwara, Ken}, booktitle = {Understanding Social Behavior in Dyadic and Small Group Interactions}, pages = {204--217}, year = {2022}, editor = {Palmero, Cristina and Jacques Junior, Julio C. S. and Clapés, Albert and Guyon, Isabelle and Tu, Wei-Wei and Moeslund, Thomas B. and Escalera, Sergio}, volume = {173}, series = {Proceedings of Machine Learning Research}, month = {16 Oct}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v173/dunbar22a/dunbar22a.pdf}, url = {https://proceedings.mlr.press/v173/dunbar22a.html}, abstract = {Interpersonal synchrony is when two parties in an interaction engage similarly due to the rhythmic coordination of their behavioral patterns. The study of synchrony in communication and psychology dates back to the 1960s but has evolved over time. Historically, studying synchrony has involved the manual coding of nonverbal cues by trained human coders, such as counting the occurrence of a specific behavior or making subjective ratings about a speaker. However, its time-consuming nature has been a serious barrier to the development of the field and has made it difficult for new scholars to adopt the technique. Recent advances in automated coding techniques allow researchers to collect nonverbal behavioral data effectively and objectively, and in a much more efficient manner than laborious manual coding methods historically relied upon. This chapter will review some of the theoretical and methodological challenges in studying interpersonal synchrony and propose alternatives using automated computer vision techniques.} }
Endnote
%0 Conference Paper %T Automated Methods to Examine Nonverbal Synchrony in Dyads %A Norah E. Dunbar %A Judee K. Burgoon %A Ken Fujiwara %B Understanding Social Behavior in Dyadic and Small Group Interactions %C Proceedings of Machine Learning Research %D 2022 %E Cristina Palmero %E Julio C. S. Jacques Junior %E Albert Clapés %E Isabelle Guyon %E Wei-Wei Tu %E Thomas B. Moeslund %E Sergio Escalera %F pmlr-v173-dunbar22a %I PMLR %P 204--217 %U https://proceedings.mlr.press/v173/dunbar22a.html %V 173 %X Interpersonal synchrony is when two parties in an interaction engage similarly due to the rhythmic coordination of their behavioral patterns. The study of synchrony in communication and psychology dates back to the 1960s but has evolved over time. Historically, studying synchrony has involved the manual coding of nonverbal cues by trained human coders, such as counting the occurrence of a specific behavior or making subjective ratings about a speaker. However, its time-consuming nature has been a serious barrier to the development of the field and has made it difficult for new scholars to adopt the technique. Recent advances in automated coding techniques allow researchers to collect nonverbal behavioral data effectively and objectively, and in a much more efficient manner than laborious manual coding methods historically relied upon. This chapter will review some of the theoretical and methodological challenges in studying interpersonal synchrony and propose alternatives using automated computer vision techniques.
APA
Dunbar, N.E., Burgoon, J.K. & Fujiwara, K.. (2022). Automated Methods to Examine Nonverbal Synchrony in Dyads. Understanding Social Behavior in Dyadic and Small Group Interactions, in Proceedings of Machine Learning Research 173:204-217 Available from https://proceedings.mlr.press/v173/dunbar22a.html.

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