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Sociolinguistic interaction and identity construction

The view from game-theoretic pragmatics

Bibliographic Data

ID3620006
AuthorsHeather Burnett (0000-0002-7389-0679, CNRS‐Université de Paris Diderot France, corresponding author)
Year2017
Volume21
Issue2
Pages238-271
Publication date2017-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Sociolinguistics (JOURNAL)
Journal identifiersISSN: 1360-6441 • E-ISSN: 1467-9841
PublisherWiley (PUBLISHER • GB)
DOI10.1111/josl.12229
OpenAlexW2610231086
LanguageEN
Citations received25
References cited68

Understanding the dynamics that characterize interaction between conversational participants is a fundamental goal of most theories of socially conditioned language use and identity construction through language. In this paper, I outline a class of formal tools that, I suggest, can be helpful in making progress towards this goal. More precisely, this paper explores how Bayesian signalling game models can be used to formalize key aspects of current sociolinguistic theories, and, in doing so, contribute to our knowledge of how speakers use their linguistic resources to communicate information and carve out their place in the social world. The Bayesian framework has become increasingly popular for the analysis of pragmatic phenomena of many different types, and, more generally, these models have become a dominant paradigm for the explanation of non-linguistic cognitive processes. As such, I argue that this approach has the potential to yield a formalized theory of personal and social identity construction and to situate the study of sociolinguistic interaction within a broader theory of rationalistic cognition

Class (philosophy · Cognition · Cognitive science · Epistemology · Identity (music · Linguistics · Pragmatics · Social group · Social identity theory · Sociolinguistics · Sociology · Computer Science · Language, Discourse, Communication Strategies · Linguistic Variation and Morphology · Psychology · Social Psychology · Syntax, Semantics, Linguistic Variation · Artificial Intelligence

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Unique citing works25
Citations per year3,57
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 23

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