Behavior Matching in Multimodal Communication Is Synchronized

Louwerse, Max M.; Dale, Rick; Bard, Ellen Gurman; Jeuniaux, Patrick

doi:10.1111/j.1551-6709.2012.01269.x

Cited by 252 publications

(331 citation statements)

References 64 publications

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“…By combining research into these and other channels, the field can better understand the functions of interpersonal synchrony. Further investigations into cross-channel questions will serve to complement the findings of early efforts in these issues (e.g., Louwerse et al, 2012).…”

Section: Future Directionsmentioning

confidence: 99%

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Frame-differencing methods for measuring bodily synchrony in conversation

2012

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The study of interpersonal synchrony examines how interacting individuals grow to have similar behavior, cognition, and emotion in time. Many of the established methods of analyzing interpersonal synchrony are costly and timeconsuming; the study of bodily synchrony has been especially laborious, traditionally requiring researchers to hand-code movement frame by frame. Because of this, researchers have been searching for more efficient alternatives for decades. Recently, some researchers (e.g., Nagaoka & Komori (IEICE Transactions on Information and Systems, 91(6), [1634][1635][1636][1637][1638][1639][1640] 2008); Ramseyer & Tschacher, 2008) have applied computer science and computer vision techniques to create framedifferencing methods (FDMs) to simplify analyses. In this article, we provide a detailed presentation of one such FDM, created by modifying and adding to existing FDMs. The FDM that we present requires little programming experience or specialized equipment: Only a few lines of MATLAB code are required to execute an automated analysis of interpersonal synchrony. We provide sample code and demonstrate its use with an analysis of brief, friendly conversations; using linear mixed-effects models, the measure of interpersonal synchrony was found to be significantly predicted by time lag (p < .001) and by the interaction between time lag and measures of interpersonal liking (p < .001). This pattern of results fits with existing literature on synchrony. We discuss the current limitations and future directions for FDMs, including their use as part of a larger methodology for capturing and analyzing multimodal interaction.Keywords Synchrony . Movement . Liking . Alignment . Frame-differencing methods . Image processing . MATLAB Conversation is arguably one of the most common-and important-modes of social interaction. Combining a variety of intrapersonal and interpersonal mechanisms, conversation presents a rich source of data for researchers in numerous areas, from linguistics and affect to posture and gesture. Interpersonal synchrony research lies at the intersection of many of these areas, seeking to characterize the way that interlocutors (individuals involved in conversation) grow to have similar behavior, cognition, and emotion over time. Many areas of research in the behavioral sciences have approached the issue of synchrony, resulting in a scattered terminology: accommodation

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Section: Future Directionsmentioning

confidence: 99%

“…Researchers are beginning to find evidence of interpersonal synchrony across a number of channels (Louwerse, Dale, Bard, & Jeuniaux, 2012). We believe that cross-channel Fig.…”

Section: Future Directionsmentioning

confidence: 99%

Frame-differencing methods for measuring bodily synchrony in conversation

2012

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“…Structured cognitive behavior can be described at multiple levels, and our thoughts both depend on and determine the social structures that contain us as elements. Often times, an apt unit of analysis is a group of people rather than an individual person (Hutchins, 1995;Louwerse, Dale, Bard, & Jeuniaux, 2012). Even when a thought is possessed by an individual and has a content that is not directly social, the nature of that thought is influenced by others.…”

Section: The Consequences Of Groups For Individual Cognitionmentioning

confidence: 99%

Social Learning Strategies in Networked Groups

2013

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When making decisions, humans can observe many kinds of information about others' activities, but their effects on performance are not well understood. We investigated social learning strategies using a simple problem-solving task in which participants search a complex space, and each can view and imitate others' solutions. Results showed that participants combined multiple sources of information to guide learning, including payoffs of peers' solutions, popularity of solution elements among peers, similarity of peers' solutions to their own, and relative payoffs from individual exploration. Furthermore, performance was positively associated with imitation rates at both the individual and group levels. When peers' payoffs were hidden, popularity and similarity biases reversed, participants searched more broadly and randomly, and both quality and equity of exploration suffered. We conclude that when peers' solutions can be effectively compared, imitation does not simply permit scrounging, but it can also facilitate propagation of good solutions for further cumulative exploration.

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“…Neural alignment during coordinated behaviour might allow access to others' states and a 'sameness recognition' [122,155], and thus provide an important grounding for social cognition and a scaffold for communication [155,156]. In conversation, movement synchrony may serve as a low-level aid to realign speakers when higher level communication breaks down [157]. At the level of the brain, rhythmic coordination can be used to promote neural alignment, which could improve joint action, communication, neural efficiency and thus social bonding [158].…”

Section: (B) Social Consequences Of Interpersonal Coordinationmentioning

confidence: 99%

Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination

Keller

Novembre

Hove

2014

Phil. Trans. R. Soc. B

329

322

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Human interaction often requires simultaneous precision and flexibility in the coordination of rhythmic behaviour between individuals engaged in joint activity, for example, playing a musical duet or dancing with a partner. This review article addresses the psychological processes and brain mechanisms that enable such rhythmic interpersonal coordination. First, an overview is given of research on the cognitive-motor processes that enable individuals to represent joint action goals and to anticipate, attend and adapt to other's actions in real time. Second, the neurophysiological mechanisms that underpin rhythmic interpersonal coordination are sought in studies of sensorimotor and cognitive processes that play a role in the representation and integration of self- and other-related actions within and between individuals' brains. Finally, relationships between social–psychological factors and rhythmic interpersonal coordination are considered from two perspectives, one concerning how social-cognitive tendencies (e.g. empathy) affect coordination, and the other concerning how coordination affects interpersonal affiliation, trust and prosocial behaviour. Our review highlights musical ensemble performance as an ecologically valid yet readily controlled domain for investigating rhythm in joint action.

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Behavior Matching in Multimodal Communication Is Synchronized

Cited by 252 publications

References 64 publications

Frame-differencing methods for measuring bodily synchrony in conversation

Frame-differencing methods for measuring bodily synchrony in conversation

Social Learning Strategies in Networked Groups

Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination

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