Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties

Area of Science:

• Social cognition
• Human-computer interaction
• Movement analysis

Background:

• Social cognition research increasingly emphasizes real-time social interaction.
• Studying complex social dynamics requires methods analyzing multiple temporal and spatial scales.
• Existing methods may not fully capture the interplay between subjective and objective factors in social coordination.

Purpose of the Study:

• To demonstrate the value of an extended multi-scale approach for analyzing embodied dyadic interaction.
• To investigate the relationship between social awareness and social coordination using movement time-series data.
• To explore fractal scaling and complexity matching in non-verbal social interaction.

Main Methods:

• Re-analysis of movement time-series data from a perceptual crossing experiment in virtual reality.
• Application of reduced movement variability analysis to identify interdependence between social awareness and coordination.
• Utilizing clustering statistics (Allan Factor) to reveal fractal scaling and complexity matching in dyadic interactions.

Main Results:

• Reduced movement variability identified an interdependence between social awareness and coordination, particularly when subjective and objective conditions converged.
• Fractal scaling was observed in salient events, with complexity matching being more pronounced in interacting pairs than surrogate dyads.
• Successful joint interaction in the perceptual crossing experiment correlated with increased local coordination.

Conclusions:

• Interpersonal interaction dynamics, analyzed through multi-scale approaches, are crucial for understanding social cognition.
• Movement variability and complexity matching offer novel insights into the constitutive role of interaction in social perception.
• A local coordination pattern emerges within complex dyadic interactions, enabling successful joint performance in tasks like the perceptual crossing experiment.