The social-dance: Decomposing naturalistic dyadic interaction dynamics to the 'micro-level.

Caroline Whyatt, Elizabeth B. Torres

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)


The 'social dance' is an implicit, yet vital, characteristic of dyadic interactions. Attempts to characterize this complex behavior have illustrated unconscious levels of content and temporal entrainment within artificial social contexts. Yet, when viewed in a naturalistic setting, this complex systems problem faces a number of methodological and theoretical challenges. Utilizing precise kinematic recordings while adopting the 'micro-movement' approach, cross coherence analysis and tenets of graph theory, this paper presents an analytical framework to characterize unfolding, nonlinear temporal exchange and entrainment across a social dyad. This framework is empirically demonstrated within a clinical domain of individuals with known social difficulties: Autism Spectrum Disorder (ASD). Results illustrate the ability for this objective methodology to quantify variability in social dynamics, and profile dyadic entrainment during naturalistic exchange -- with no a priori constraints or limitations. Viewed within the context of a clinical assessment tool for ASD, results facilitate consideration of clinician impact on dyadic exchange, and point to a potential refinement of core tasks associated with such clinical batteries
Original languageEnglish
Number of pages8
Publication statusPublished - 28 Jun 2017
EventInternational Conference on Movement Computing - Goldsmiths University, London
Duration: 28 Jun 201730 Jun 2017
Conference number: 4th


ConferenceInternational Conference on Movement Computing


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