Goodwin, Aurora
2022.
Keepin’ it real: Performing authenticity on Twitter
disinformation accounts.
PhD Thesis,
Cardiff University.
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Abstract
Disinformation is information that is shared with the intention to mislead (Fallis 2015). In 2017, it was revealed that online personas who gained sizeable Twitter followings were part of a large-scale disinformation campaign that aimed to undermine public trust in American democratic systems, specifically the 2016 Presidential Election. According to the United States Department of Justice (2018:15), content was evaluated to ensure it ‘appeared authentic- as if operated by U.S. persons’. This thesis adopts a discourse analytic perspective and examines how disinformation accounts associated with the campaign constructed authentic personas on Twitter. The data used in this thesis draws on a publicly accessible dataset of accounts and tweets that were part of the aforementioned campaign. Although some discussions of disinformation prioritise an approach to authenticity as an essential quality, this study approaches authenticity as a discursive performance. Performances of authenticity are analysed from linguistic, visual, and narrative analytic perspectives to address the following questions: How are handles, usernames, and profile pictures employed for authenticating identity performance on Twitter disinformation accounts? How do disinformation accounts manage (co-)tellership to (dis)identify with different social groups when storying a particular news event? This thesis reveals that across handles, usernames, and profile pictures, authenticity is achieved by appropriating established norms and practices primarily associated with two types of accounts: those belonging to individuals and those that share news. At the same time, the accounts’ narration of a high-profile news story reinforces the identity aspects presented in naming strategies and profile pictures, contributing to valid representations of particular personas. I argue that the disinformation accounts perform a particular type of authenticity, which can be referred to as: authenticity at-a-glance. I suggest that authenticity at-a-glance draws on the adoption of established practices of identification on Twitter that are readily accessible to viewers (via metadata units and tweet content) and orients to pre-existing social and political stereotypes.
Item Type: | Thesis (PhD) |
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Date Type: | Completion |
Status: | Unpublished |
Schools: | English, Communication and Philosophy |
Funders: | ESRC |
Date of First Compliant Deposit: | 2 May 2023 |
Last Modified: | 02 May 2024 01:30 |
URI: | https://orca.cardiff.ac.uk/id/eprint/159123 |
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