Attitudes, communicative functions, and lexicogrammatical features of anti-vaccine discourse on Telegram

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AT32DE82F" target="_blank" >RIV/00216208:11320/25:T32DE82F - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2666799124000121" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2666799124000121</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.acorp.2024.100095" target="_blank" >10.1016/j.acorp.2024.100095</a>

Result language

angličtina

Original language name

Attitudes, communicative functions, and lexicogrammatical features of anti-vaccine discourse on Telegram

Original language description

This paper reports the process of collecting a corpus with examples of anti-vaccine discourse and the results of its linguistic analysis. The overall aim of the project is to help public health authorities to improve their communication campaigns by better understanding the conditions for misinformation spreading via social media. More specifically, this paper analyses linguistic properties of a corpus of prominent misinformation channels in Telegram as compared against a more general COVID corpus as well as against a general purpose English corpus. For this paper, the quantitative analysis relies on corpus querying to identify the most recurrent discourse patterns related to COVID vaccines. We use the appraisal framework to analyse the patterns with respect to the attitudes conveyed in the messages. We have also applied an automatic AI classifier to predict communicative functions of these texts. This allows us to examine them more closely through the use of simple lexicogrammatical features following Biber, as well as their ideational processes following Halliday. The findings show that common collocations in the Telegram corpus containing misinformation draw on three attitudes: fear, insecurity, and mistrust in COVID vaccines which are discursively constructed to promote vaccine hesitancy among social media users. Furthermore, the misinformation messages tend to occur more often in such communicative functions as promotional texts, news reporting, and text expressed as presenting reference information.

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Applied Corpus Linguistics

ISSN

2666-7991

e-ISSN

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Volume of the periodical

4

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

1-9

UT code for WoS article

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EID of the result in the Scopus database

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