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  5. The Remediation of Paralinguistic Features for the Construction of Epistemic Stance in Online Vegan Communities
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The Remediation of Paralinguistic Features for the Construction of Epistemic Stance in Online Vegan Communities

Date Issued
August 1, 2020
Author(s)
Shepard, James R III  
Advisor(s)
Jessica Grieser
Additional Advisor(s)
Lisa King
Sean Morey
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/42555
Abstract

In this thesis, I examine how members of online vegan communities construct and perform epistemic stance through exploiting the affordances of alphabetic computer-mediated communication (CMC) to remediate paralinguistic features. The data are taken from two exchanges across two different online platforms: Facebook and Reddit. Working within the constraints of alphabetic CMC and the affordances of their respective platforms, interactants discuss vegan activism in ways that mimic traditional oral communication. Utilizing unique linguistic constructions and features of CMC such as emoji and emoticons, interactants are able to clearly perform their affective and epistemic stances as well as demonstrate what McCulloch calls online fluency. As the exchanges take place within online vegan communities, interactants are able to discuss, evaluate, and critique vegan activists without having to justify or defend veganism as an ideology or practice. This allows for interactants to position themselves around a clear and identifiable stance-object, while simultaneously co-constructing a joint stance. Comparing the linguistic choices of users on both Facebook and Reddit allows for a clear picture of how users leverage the affordances and work within the constraints of both mediums to accomplish shared goals.

Subjects

Stancetaking

Remediation

Veganism

Activism

Internet Linguistics

Computer Mediated Com...

Disciplines
Anthropological Linguistics and Sociolinguistics
Discourse and Text Linguistics
Rhetoric and Composition
Degree
Master of Arts
Major
English
File(s)
Thumbnail Image
Name

Shepard_2020_The_Remediation_of_Paralinguistic_Features.docx

Size

2.14 MB

Format

Microsoft Word XML

Checksum (MD5)

98383595425adc0c38dd1780fefccfbc

Thumbnail Image
Name

auto_convert.pdf

Size

2.1 MB

Format

Adobe PDF

Checksum (MD5)

7b033980228269f9d2c27a8fd064611d


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