Context as Complexity in Contemporary Communication

Communication has never occupied such a pervasive and immediate place in human life. The rapid development and diffusion of language modeling and communication technologies has created conditions in which linguistic interactions unfold within a dense web of social settings, contextual signals, and digital platforms that continually reshape language use. These conditions underscore the need for foundational research on language use as it emerges from unprecedented levels of complexity. A central challenge for any such program is to develop a theory of how context affects syntactic choices and semantic interpretation. Moreover, this work must remain sensitive to the contextual pressures distinctive to the modern communication landscape. As AI-driven conversational agents become increasingly ubiquitous across industries and online social networks evolve, novel communicative contexts are continuously taking shape across scales. The emergence of these contexts inevitably raises questions about the robustness of existing findings across fields in which situated language use is a key observable---including computational linguistics, media studies, and computational social science. Such questions become especially prescient as these new forms of communication are being introduced into high-stakes domains such as health, politics, and law. The dissertation proposed advances this project by adopting complexity theory as a meta-theoretical lens for pragmatics and sociolinguistics. Both of these disciplines offer rich theoretical traditions and empirical findings that illuminate how social and communicative contexts shape linguistic form and meaning. However, methods for extending concepts and measurements in both pragmatics and sociolinguistics in ways that support computational analysis are still under active development. Adopting a complex systems approach enables us to address this task by operationalizing existing constructs in both fields as measurable quantities, while still preserving their theoretical commitments. This move also reflects an ontological position that treats contextual effects as central to the process of inferring meaning in the complex, adaptive, and slowly-evolving system of signs and conventions which govern language use. The proposed dissertation’s contributions unfold across three studies that conceptualize context as operating on three scales--- both as a site of convergence and as a source of variation. Beginning with contextual effects on the order of single utterances, I present original research on the pragmatics of state-of-the-art language models, combining formal and statistical methods to provide evidence that reasoning about context in modern AI systems exhibits fundamental instabilities. Moving to group-level interactions, I propose an observational study examining the sociolinguistic status of Bluesky Starter Packs. Finally, at the population level, I introduce a mathematical model that explicitly encodes the inferential processes underlying situated language use, enabling the approximation of informational constraints on communication in social networks.