37.2805, Diss: English; Cognitive Science, Computational Linguistics, Philosophy of Language, Pragmatics: Sagar Kumar: "Context as Complexity in Contemporary Communication"

Wed Sep 2 18:05:02 UTC 2026

LINGUIST List: Vol-37-2805. Wed Sep 02 2026. ISSN: 1069 - 4875.

Subject: 37.2805, Diss: English; Cognitive Science, Computational Linguistics, Philosophy of Language, Pragmatics: Sagar Kumar: "Context as Complexity in Contemporary Communication"

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Date: 02-Sep-2026
From: Sagar Kumar [kumar.sag at northeastern.edu]
Subject: Context as Complexity in Contemporary Communication

Institution: Northeastern University
Degree Date: 2026
Level: PhD

Author: Sagar Kumar

Dissertation Title: Context as Complexity in Contemporary
Communication

Dissertation URL: https://www.proquest.com/docview/3378584023

Linguistic Field(s): Cognitive Science
                     Computational Linguistics
                     Philosophy of Language
                     Pragmatics

Subject Language(s): English (eng, stan1293)

Dissertation Director(s): Brooke Foucault Welles

Dissertation Abstract:

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.
This dissertation advances this project by adopting complexity theory
as a meta-theoretical lens for pragmatics. As the study of meaning in
context, pragmatics offers a rich theoretical tradition and empirical
findings that illuminate how social and communicative contexts shape
linguistic form and meaning. However, methods for extending concepts
and measurements in the field 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 the field as measurable quantities, while still
preserving their theoretical commitments. This move also reflects an
ontological position that treats context as describing the broken
symmetries from which meaning emerges within the complex, adaptive,
and slowly-evolving system of signs and conventions which govern
language use. Each study accordingly identifies an invariance that
should hold if context were inert, and measures whether it does.
The dissertation's contributions unfold across three studies that
conceptualize context as operating on three scales—as a source of
instability, a site of cohesion, and a mechanism of decay. 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: theoretically inert discourse context destabilizes
model inferences, erases correlations with cultural stereotypes, and
does so, in a substantial share of cases, irreducibly. Moving to
group-level interactions, I present an observational study of Bluesky
Starter Packs providing the first platform-scale evidence for Clark
(2006)'s claim that communal common ground is graded, showing that
shared lexical repertoire grows with the number of topically distinct
communities two users share, independently of their proximity in the
social network. Finally, at the population level, I introduce an
exactly solvable mathematical model of communication as serialized
transmission over a noisy channel, showing that the fidelity with
which a population retains information about a source is governed by
the spectrum of the channel and the sparsity of the network through
which messages spread.

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