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Detecting Linguistic Characteristics of Political Disinformation in Indonesian Social Media

Insights From Systemic Functional Linguistics

Bibliographic Data

ID21804802
AuthorsPutu Nur Ayomi (0000-0002-2431-1781, Universitas Mahasaraswati Denpasar), Desak Putu Eka Pratiwi (0000-0002-4791-6169, Universitas Mahasaraswati Denpasar), Ni Wayan Krismayani (0000-0002-0120-844X, Universitas Mahasaraswati Denpasar)
Year2025
Volume16
Issue3
Pages838-848
Publication date2025-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Language Teaching and Research (JOURNAL)
Journal identifiersISSN: 1798-4769 • E-ISSN: 2053-0684
PublisherAcademy Publication (PUBLISHER • GB)
DOI10.17507/jltr.1603.14
OpenAlexW4410008499
LanguageEN
Citations received1
References cited20

This study examines the linguistic features of political disinformation on Indonesian social media during the 2024 presidential election using Systemic Functional Linguistics (SFL). The study employed a qualitative descriptive method, collecting data from Twitter (now X) and Instagram posts related to the 2024 Indonesian presidential election, focusing on posts containing clear evidence of disinformation. The analysis mapped the lexicogrammatical features of disinformation at three levels: ideational, interpersonal, and textual metafunctions to explain how these features shape the overall discourse. The study reveals frequent use of Material and Relational processes to misrepresent political figures, while Verbal processes distort statements through selective quoting. Attitude, engagement, and graduation features are also prominent, with disinformation posts expressing strong negative judgments about political opponents. Engagement techniques, such as selective citation and heteroglossia, create an illusion of balanced argument, while graduation features amplify emotional intensity through exaggerated language and forceful assertions. Disinformation posts rely on declarative clauses, rhetorical questions, and high modality to present falsehoods as factual, while causal conjunctions and marked themes enhance the coherence of biased narratives. The study underscores the need for a metalinguistic approach to social media literacy, equipping users with tools to critically analyze disinformation

Corpus linguistics · Disinformation · Indonesian · Linguistics · Political science · Politics · Social media · Sociology · Systemic functional linguistics · World Wide Web · Computer Science · Misinformation and Its Impacts · Philosophy

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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