Recent studies of dyadic interaction have examined phenomena of synchronization, entrainment, alignment, and convergence. All these forms of behavioral matching have been hypothesized to play a supportive role in establishing coordination and common ground between interlocutors. In the present study, evidence is found for a new kind of coordination termed complexity matching. Temporal dynamics in conversational speech signals were analyzed through time series of acoustic onset events. Timing in periods of acoustic energy was found to exhibit behavioral matching that reflects complementary timing in turn-taking. In addition, acoustic onset times were found to exhibit power law clustering across a range of timescales, and these power law functions were found to exhibit complexity matching that is distinct from behavioral matching. Complexity matching is discussed in terms of interactive alignment and other theoretical principles that lead to new hypotheses about information exchange in dyadic conversation and interaction in general.
Research on interpersonal convergence and synchrony characterizes the way in which interacting individuals come to have more similar affect, behaviour, and cognition over time. Although its dynamics have been explored in many settings, convergence during conflict has been almost entirely overlooked. We present a simple but ecologically valid study comparing how different situational contexts that highlight affiliation and argument impact interpersonal convergence of body movement and to what degree emotional states affect convergence in both conversational settings. Using linear mixed-effect models, we found that in-phase bodily synchrony decreases significantly during argument. However, affective changes did not significantly predict changes in levels of interpersonal synchrony, suggesting that differences in affect valences between affiliation and argument cannot solely explain our results.
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
Successful interaction requires complex coordination of body movements. Previous research has suggested a functional role for coordination and especially synchronization (i.e., time-locked movement across individuals) in different types of human interaction contexts. Although such coordination has been shown to be nearly ubiquitous in human interaction, less is known about its function. One proposal is that synchrony supports and facilitates communication (Topics Cogn Sci 1:305-319, 2009). However, questions still remain about what the properties of coordination for optimizing communication might look like. In the present study, dyads worked together to construct towers from uncooked spaghetti and marshmallows. Using cross-recurrence quantification analysis, we found that dyads with loosely coupled gross body movements performed better, supporting recent work suggesting that simple synchrony may not be the key to effective performance (Riley et al. 2011). We also found evidence that leader-follower dynamics-when sensitive to the specific role structure of the interaction-impact task performance. We discuss our results with respect to the functional role of coordination in human interaction.
Dynamic patterns of influence between parents and children have long been considered key to understanding family relationships. Despite this, most observational research on emotion in parent–child interactions examines global behaviors at the expense of exploring moment-to-moment fluctuations in emotions that are important for relational outcomes. Using recurrence quantification analysis (RQA) and growth curve analysis, this investigation explored emotion dynamics during parent–adolescent conflict interactions, focusing not only on concurrently shared emotional states but also on time-lagged synchrony of parents’ and adolescents’ emotions relative to one another. Mother–adolescent dyads engaged in a 10-min conflict discussion and reported on their satisfaction with the process and outcome of the discussion. Emotions were coded using the Specific Affect Coding System (SPAFF) and were collapsed into the following categories: negativity, positivity, and validation/interest. RQA and growth curve analyses revealed that negative and positive emotions were characterized by a concurrently synchronous pattern across all dyads, with the highest recurrence rates occurring around simultaneity. However, lower levels of concurrent synchrony of negative emotions were associated with higher discussion satisfaction. We also found that patterns of negativity differed with age: Mothers led negativity in dyads with younger adolescents, and adolescents led negativity in dyads with older adolescents. In contrast to negative and positive emotions, validation/interest showed the time-lagged pattern characteristic of turn-taking, and more highly satisfied dyads showed stronger patterns of time-lagged coordination in validation/interest. Our findings underscore the dynamic nature of emotions in parent–adolescent interactions and highlight the important contributions of these moment-to-moment dynamics toward overall interaction quality.
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