Detecting Linguistic Characteristics of Political Disinformation in Indonesian Social Media: Insights From Systemic Functional Linguistics
DOI:
https://doi.org/10.17507/jltr.1603.14Keywords:
disinformation, social media, systemic functional linguisticsAbstract
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.
References
Anghel, R. (2021). From ‘the New Man’ to care‐leaver activists—Communist and contemporary discourses shaping 50 years of leaving care in Romania. Child & Family Social Work, 26(2), 258–269. https://doi.org/10.1111/cfs.12819
Annur, C. M. (2024). In Media Sosial Paling Banyak Digunakan di Indonesia Awal 2024. Retrieved March 5, 2024, from https://databoks.katadata.co.id/datapublish/2024/03/01/ini-media-sosial-paling-banyak-digunakan-di-indonesia-awal-2024
Ardi, N., Ahmad, A., Daud, N., & Ismail, N. (2021). Speech Act of Flaming in Twitter Status. Asian Journal of University Education, 16(4), 109. https://doi.org/10.24191/ajue.v16i4.11961
Ayomi, P. N. (2021a). Managing Interpersonal Meaning in Social Media: a Case Study of Indonesian Language Use. Academic Journal Perspective: Education, Language and Literature, 9(1), 1–14. https://doi.org/10.33603/perspective.v9i1
Ayomi, P. N. (2021b). Trump vs Jokowi: Exploring the Lexicogrammatical Variation of Head of States’ Twitter Communication. LITERA, 20(1), 179–195. https://doi.org/10.21831/ltr.v20i1.34554
Ayomi, P. N. (2022). Realisasi Makna Sikap Sebagai Pengungkap Pendirian Dalam Percakapan Tentang Vaksinasi COVID-19 Di Twitter. Aksara, 34(1), 121–134. https://doi.org/10.29255/aksara.v34i1.814.121-134
Ayomi, P. N., Candra, K. D. P., & Sulatra, I. K. (2023). Speech act and experiential analysis of Bali netizen reactions to the pandemic regulation posts. Rainbow: Journal of Literature, Linguistics and Culture Studies, 12(2), 86–92. https://doi.org/10.15294/rainbow.v12i2.59090
Cao, F. (2023). Engagement resources in the English news texts of two phases in China’s constructing Greater Bay Area. Cogent Arts & Humanities, 10(1). https://doi.org/10.1080/23311983.2023.2243076
Dame Adjin-Tettey, T. (2022). Combating fake news, disinformation, and misinformation: Experimental evidence for media literacy education. Cogent Arts & Humanities, 9(1). https://doi.org/10.1080/23311983.2022.2037229
Dunmire, P. L. (2012). Political Discourse Analysis: Exploring the Language of Politics and the Politics of Language. Language and Linguistics Compass, 6(11), 735–751. https://doi.org/10.1002/lnc3.365
Edgerly, S., & Thorson, K. (2020). Political Communication and Public Opinion. Public Opinion Quarterly, 84(S1), 189–194. https://doi.org/10.1093/poq/nfaa019
Fairclough, N. (1992). Discourse and Social Change. (Polity Press., Ed.). Cambridge.
Farkas, J., & Schou, J. (2020). Post-Truth, Fake News, and Democracy: Mapping the Politics of Falsehood. Routledge.
Freiling, I., Krause, N. M., Scheufele, D. A., & Brossard, D. (2023). Believing and sharing misinformation, fact-checks, and accurate information on social media: The role of anxiety during COVID-19. New Media & Society, 25(1), 141–162. https://doi.org/10.1177/14614448211011451
Halliday, M. A. K. (1978). Language as Social Semiotic: the Social Interpretation of Language and Meaning. London: Edward Arnold.
Halliday, M. A. K., & Matthiessen, C. M. I. (1999). Construing experience through meaning: a language-Based Approach to Cognition. London: Cassell.
Halliday, M. A. K., & Matthiessen, C. M. I. (2014). An introduction to functional grammar (4th ed.). London: Edward Arnold.
Hameleers, M., & van der Meer, T. G. L. A. (2020). Misinformation and Polarization in a High-Choice Media Environment: How Effective Are Political Fact-Checkers? Communication Research, 47(2), 227–250. https://doi.org/10.1177/0093650218819671
Horner, C. G., Galletta, D., Crawford, J., & Shirsat, A. (2021). Emotions: The Unexplored Fuel of Fake News on Social Media. Journal of Management Information Systems, 38(4), 1039–1066. https://doi.org/10.1080/07421222.2021.1990610
Ireton, C., & Posetti, J. (2018). Journalism, ‘Fake news’ & Disinformation. Handbook for Journalism Education and Training. UNESCO.
Iswatiningsih, D., Andalas, E. F., & Inayati, N. (2019). Hate Speech by Supporters of Indonesian Presidential Candidates on Social Media. In Proceedings of the 6th International Conference on Community Development (ICCD 2019). Paris, France: Atlantis Press. https://doi.org/10.2991/iccd-19.2019.35
Khan, M. L., & Idris, I. K. (2019). Recognise misinformation and verify before sharing: a reasoned action and information literacy perspective. Behaviour & Information Technology, 38(12), 1194–1212. https://doi.org/10.1080/0144929X.2019.1578828
Kozyreva, A., Wineburg, S., Lewandowsky, S., & Hertwig, R. (2023). Critical Ignoring as a Core Competence for Digital Citizens. Current Directions in Psychological Science, 32(1), 81–88. https://doi.org/10.1177/09637214221121570
Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: a systematic review. Annals of the International Communication Association, 45(3), 188–206. https://doi.org/10.1080/23808985.2021.1976070
Lebernegg, N., Eberl, J.-M., Tolochko, P., & Boomgaarden, H. (2024). Do You Speak Disinformation? Computational Detection of Deceptive News-Like Content Using Linguistic and Stylistic Features. Digital Journalism, 1–24. https://doi.org/10.1080/21670811.2024.2305792
Liardét, C. L., & Black, S. (2020). Trump vs. Trudeau: Exploring the power of grammatical metaphor for academic communication. Journal of English for Academic Purposes, 45, 100843. https://doi.org/10.1016/j.jeap.2020.100843
Lundgren, R. E., & McMakin, A. H. (Eds.). (2013). Risk Communication. Wiley. https://doi.org/10.1002/9781118645734
Marcos-García, S., Alonso-Muñoz, L., & Casero-Ripollés, A. (2021). The Influence of the Negative Campaign on Facebook: The Role of Political Actors and Citizens in the Use of Criticism and Political Attack in the 2016 Spanish General Elections. Social Sciences, 10(10), 356. https://doi.org/10.3390/socsci10100356
Marshall, N., & Bowcher, W. L. (2006). Book Review: Systemic Functional Linguistics and Critical Discourse Analysis: Studies in Social Change. Discourse & Society, 17(2), 265–270. https://doi.org/10.1177/095792650601700207
Martin, J. R., & White, P. R. R. (2005). The language of evaluation: appraisal in English. New York: Palgrave Macmillan.
Nefedova, L., & Samkova, M. (2019). Detection Of Disinformation in A Media Text (Structural And Pragma-Linguistic Approaches) (pp. 265–272). https://doi.org/10.15405/epsbs.2019.08.02.31
Sari, E. M. P., Santosa, R., Djatmika, D., & Wiratno, T. (2024). Examining Social Actors in Investment Fraud News: A Transitivity and Appraisal Analysis. Theory and Practice in Language Studies, 14(7), 2150–2160. https://doi.org/10.17507/tpls.1407.23
Sloan, L., & Quan-Haase, A. (2016). The SAGE Handbook of Social Media Research Methods. 1 Oliver’s Yard, 55 City Road London EC1Y 1SP: SAGE Publications Ltd. https://doi.org/10.4135/9781473983847
Steinert, S., Marin, L., & Roeser, S. (2022). Feeling and thinking on social media: emotions, affective scaffolding, and critical thinking. Inquiry, 1–28. https://doi.org/10.1080/0020174X.2022.2126148
Sugiono, S. (2020). Fenomena Industri Buzzer Di Indonesia: Sebuah Kajian Ekonomi Politik Media. Communicatus: Jurnal Ilmu Komunikasi, 4(1), 47–66. https://doi.org/10.15575/cjik.v4i1.7250
Suparto, A. D. (2018). Transitivity Analysis on Framing in the Online News Articles. Ranah: Jurnal Kajian Bahasa, 7(1), 16–32. https://doi.org/10.26499/rnh.v7i1.586
Tang, L. (2021). Transitive representations of China’s image in the US mainstream newspapers: A corpus-based critical discourse analysis. Journalism, 22(3), 804–820. https://doi.org/10.1177/1464884918801116
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
Weeks, B. E. (2015). Emotions, Partisanship, and Misperceptions: How Anger and Anxiety Moderate the Effect of Partisan Bias on Susceptibility to Political Misinformation. Journal of Communication, 65(4), 699–719. https://doi.org/10.1111/jcom.12164
