Human sociality is grounded in the dynamic coordination of individuals as they interact with one another. Indeed, various levels of interpersonal coordination — neural, behavioural, physiological, affective, linguistic — are hallmarks of successful social communication and cooperation. However, describing these complex, interdependent dynamics has been limited by current methodological approaches, owing to a restrictive repertoire of tools and the absence of a unified, standardized methodological framework. Here, we identify information theory — the mathematical theory of communication — as a particularly well-suited conceptual framework to address this shortfall, given its appropriate sensitivity to complex dynamics, including potential nonlinearity and higher-order interactions, and its data-driven, model-agnostic foundations. With deep roots in computational, cognitive and systems neuroscience, the formal introduction of information-theoretic quantities and methods into the study of interpersonal coordination is perhaps overdue. In this Perspective, we advance the case for a unified information-theoretic framework for the field while paving the way for a new generation of empirically testable, theoretically grounded research questions.