Bodily synchronization underlying joke telling

Abstract

Advances in video and time series analysis have greatly enhanced our ability to study the bodily synchronization that occurs in natural interactions. Past research has demonstrated that the behavioral synchronization involved in social interactions is similar to dynamical synchronization found generically in nature. The present study investigated how the bodily synchronization in a joke telling task is spread across different nested temporal scales. Pairs of participants enacted knock–knock jokes and times series of their bodily activity were recorded. Coherence and relative phase analyses were used to evaluate the synchronization of bodily rhythms for the whole trial as well as at the subsidiary time scales of the whole joke, the setup of the punch line, the two-person exchange and the utterance. The analyses revealed greater than chance entrainment of the joke teller’s and joke responder’s movements at all time scales and that the relative phasing of the teller’s movements led those of the responder at the longer time scales. Moreover, this entrainment was greater when visual information about the partner’s movements was present but was decreased particularly at the shorter time scales when explicit gesturing in telling the joke was performed. In short, the results demonstrate that a complex interpersonal bodily “dance” occurs during structured conversation interactions and that this “dance” is constructed from a set of rhythms associated with the nested behavioral structure of the interaction.

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

“…Specifically, both frequency and amplitude of the time-series here assessed notably change over different time windows entailing that the dynamics of the behavioral data depend on the scale that is being taken into account. Therefore, our study supports the intuition (Bedia et al, 2014; Schmidt et al, 2014) that dyadic social interaction analysis should not be limited to short time scales alone and that a thorough evaluation (such as time-series analysis) of the phenomenon is required in order to gain a better understanding of it. In Sections “Movement Invariants in the Frequency and Time Domains Classify Social Interaction” and “PCE As a Minimal Dyadic Conversation,” the different types of analysis applied in this research are discussed.…”

“…In the context of embodied social interaction, the slower time scales involving conversation and body movements have been shown to mediate important parts of the social exchange (Schmidt et al, 2014). Bedia et al (2014) confirmed the multi-scale character of human–human interaction in a modified and constrained version of the PCE.…”

Foregrounding Sociomaterial Practice in Our Understanding of Affordances: The Skilled Intentionality Framework

“…The sociomateriality of the landscape of affordances in flux urges the study of social coordination to include coordination with materiality, i.e., as sociomaterial synergies. Moreover, zooming out emphasizes a focus not just at the scale of immediate interpersonal (e.g., dyadic) interaction, but to also include nesting scales of coordinating (Wijnants et al, 2012; Schmidt et al, 2014) with more distant dealings and places (Heft, 1996; Bruineberg and Rietveld, 2014; Van Dijk and Withagen, 2016) and perhaps even entire practices (Rietveld and Brouwers, 2016) and language games (Rietveld and Kiverstein, 2014; Van Dijk, 2016). Furthermore, from a lived perspective, one never encounters an affordance in isolation.…”

Triadic Synchrony: Application of Multiple Wavelet Coherence to a Small Group Conversation

“…Reference [18] performed a rhythmical sway task in the sagittal plane, and found that a light fingertip contact, i.e., haptic contact, increased coherence. In settings with more socialization, [19] used a periodic interaction task (knock-knock joking task), and calculated wavelet coherence to evaluate rhythmic similarity between two individuals. Not employing specific rhythmic task, [13] illustrated that synchrony could be evaluated by using wavelet coherence even in unstructured conversation situation.…”

“…However, previous studies employing the wavelet approach [13] [17]- [19] have shed light on the dyadic interaction; it is still unquestioned whether synchrony can be captured in a small group interaction. To handle this issue, as a first step, this study focused on triadic interaction, and tried to measure the overall synchrony from three individuals engaging a brainstorming task, a well-known small group task in an office meeting situation.…”