Social and nonlinear dynamics unite: musical group synchrony

Demos, Alexander P.; Palmer, Caroline

doi:10.1016/j.tics.2023.05.005

Cited by 14 publications

(9 citation statements)

References 81 publications

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“…The question of synchrony or other forms of coordination during large group interactions has been investigated in the relatively structured social interactions of musical participation, and increasingly, it is being recognized that the behavior of a large interacting group may not be wholly explained by description of local interactions alone, but rather by description of the emergent dynamics of the group itself (Demos & Palmer, 2022;Høffding et al, 2023;Schiavio, Maes, & van der Schyff, 2022). We argue that the methods used to study these musical social interactions (from coordination dynamics and dynamical systems, c.f.…”

Section: Introductionmentioning

confidence: 99%

“…Farrera and Ramos-Fernández (2022) describe a phenomenon of emergent collective rhythm (like the collective "wave") as the emergence of "group-level rhythmic patterns" that result from the self-organization of social behavior through entrainment and synchronization (Farrera & Ramos-Fernández, 2022). This social behavior is characterized by "context-specific interactions" and mutual "fast adaptation to other group members" actions' (Demos & Palmer, 2022). This coordinated crowd behavior at sporting events can include both the physical movement of the crowd and variations of coordinated or rhythmic auditory signals generated by their cheers and chants.…”

Section: Introductionmentioning

confidence: 99%

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Recurrence Quantification Analysis of Crowd Sound Dynamics

Proksch,

Reeves,

Gee

et al. 2023

Cognitive Science

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When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recurrence Quantification Analysis of Crowd Sound Dynamics

Proksch,

Reeves,

Gee

et al. 2023

Cognitive Science

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show abstract

“…Although it is justifiable to apply GC to short time series in contexts where there is no alternative, such as non-human animal communicative signalling, and when done in parallel with complementary methods [ 98 ], in our view, the appropriateness of doing so for human musical interaction requires further investigation. Ultimately, it will be beneficial to explore alternative metrics and modelling techniques to capture dynamics of the strength and directionality of coupling in musical groups [ 86 , 99 , 100 ].…”

Section: Discussionmentioning

confidence: 99%

Leadership dynamics in musical groups: Quantifying effects of musical structure on directionality of influence in concert performance videos

Sabharwal,

Breaden,

Volpe

et al. 2024

PLoS ONE

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Music ensemble performance provides an ecologically valid context for investigating leadership dynamics in small group interactions. Musical texture, specifically the relative salience of simultaneously sounding ensemble parts, is a feature that can potentially alter leadership dynamics by introducing hierarchical relationships between individual parts. The present study extended previous work on quantifying interpersonal coupling in musical ensembles by examining the relationship between musical texture and leader-follower relations, operationalised as directionality of influence between co-performers’ body motion in concert video recordings. It was hypothesised that the directionality of influence, indexed by Granger Causality, would be greater for ‘homophonic’ textures with a clear distinction between melody and accompaniment parts than for ‘polyphonic’ textures with less distinction between melody and accompaniment. This hypothesis was tested by using pose estimation algorithms to track instrumentalists’ body movements in a string quartet and a clarinet quintet, and then applying Granger Causality analysis to their head motion to estimate directional influence between instrumentalist pairs for sections of the pieces that varied in texture. It was found that Granger Causality values were generally higher (indicating greater directionality of influence) for homophonic than polyphonic textures. Furthermore, considering melody and accompaniment instrument roles revealed more evidence for the melody instrument influencing accompanying instruments than vice versa, plus a high degree of directionality among accompanying instruments, in homophonic textures. These observed patterns of directional information flow in co-performer body motion are consistent with changing leader-follower relations depending on hierarchical relations between ensemble parts in terms of the relative salience of melodic material in the musical texture. The finding that automatic pose estimation can detect modulations of leadership dynamics in standard video recordings under naturalistic performance conditions has implications for investigating interpersonal coordination in large-scale music video datasets representing different cultural traditions, and for exploring nonverbal communication in group activities more generally.

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“…Quantifying the synchrony of a group requires different statistical methods (Baranowski-Pinto et al, 2022;Richardson et al, 2012;S. H. Strogatz, 2000), such as the incorporation of network analysis (Bonnell et al, 2022) or the estimation of entropy (Demos & Palmer, 2023).…”

Section: Across Space and Time: Multimodal And Multiscale Approachesmentioning

confidence: 99%

How and Why People Synchronize: An Integrated Perspective

daSilva,

Wood

2024

Preprint

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Interpersonal synchrony, the alignment of behavior and/or physiology during interactions, is a pervasive phenomenon observed in diverse social contexts. Here we synthesize across contexts and behaviors to classify the different forms and functions of synchrony. We provide a concise framework for classifying the manifold forms of synchrony along six dimensions: periodicity, discreteness, spatial similarity, directionality, leader-follower dynamics, and observability. We also distill the various proposed functions of interpersonal synchrony to four interconnected functions: reducing complexity and improving understanding, accomplishing joint tasks, strengthening social connection, and influencing partners’ behavior. These functions derive from first principles, emerge from each other, and are accomplished by some forms of synchrony more than others. Effective synchrony flexibly adapts to social goals and more synchrony is not always better. Our synthesis offers a shared framework and language for the field, allowing for better cross-context and cross-behavior comparisons, generates new hypotheses, and highlights future research directions.

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Social and nonlinear dynamics unite: musical group synchrony

Cited by 14 publications

References 81 publications

Recurrence Quantification Analysis of Crowd Sound Dynamics

Recurrence Quantification Analysis of Crowd Sound Dynamics

Leadership dynamics in musical groups: Quantifying effects of musical structure on directionality of influence in concert performance videos

How and Why People Synchronize: An Integrated Perspective

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