Complexity Matching in Dyadic Interaction

Conversation is a complex coordination of human behaviours (Riley, Richardson, Shockley, & Ramenzoni, 2011). Recent theoretical discussion of dyadic coordination has focused on issues of synchronization, entrainment, alignment, and convergence. All of these terms refer to a local matching of specific behavioural and linguistic events, such that members of a dyad coordinate by “doing the same thing.” Though much research has studied dyadic coordination that goes beyond mere synchrony, few studies have analysed dynamics beyond synchrony and phase. Communicative behaviours tend to be highly variable, irregular, and heterogeneous, like most human behaviours. Therefore, it appears that there could be more complex temporal patterns, beyond local matching and into the management of more complex dynamics of interaction. More complex patterns are often expressed by heavy-tailed distributions (i.e., heavier than an exponential fall off) that reflect variations across wide ranges of timescales. For instance, long-run variations in the acoustics of speech signals are known to follow a pattern of so-called “1/f noise”—irregular fluctuations in amplitude occur across a wide range of frequencies yet fall into a power law relationship with each other (Voss & Clark, 1978). The term complexity matching was recently coined by West and colleagues to refer to the concept that interacting complex systems may become coordinated in a way that is reflected in distributional and temporal measures of their complexity (West, Geneston, & Grigolini, 2008). In particular, the statistical shapes of their complexities should have a tendency to match up. This tendency is hypothesized to be adaptive because models exhibit maximal information transmission between them when the complexities of their activities match up. In the present study, we tested whether complexity matching can be detected between conversational partners and if different conversational contexts constrain the dynamics differentially.