Unveiling Political Bias in English Newspapers of Indonesian News Portal: A Critical Discourse Analysis Approach

Authors

  • Faza Afifah Ghina Putri Abdilah Pendidikan Bahasa Inggris, FBS Universitas Negeri Semarang , Indonesia
  • Izzati Gemi Seinsiani Pendidikan Bahasa Inggris, FBS Universitas Negeri Semarang , Indonesia

DOI:

https://doi.org/10.24256/ideas.v13i2.9703

Keywords:

Critical Discourse Analysis (CDA), Indonesian news portals, media framing, political bias, pro-government bias

Abstract

English language news portals have become important cites where political narratives are built for both local and global viewers as press freedom wanes in Indonesia and media ownership grows more concentrated. Although Indonesian media has seen increasing academic attention, few studies using Critical Discourse Analysis (CDA) have looked at how pro-government bias works linguistically in English-language political coverage during electoral cycles. Using Fairclough's three-dimensional CDA model on 25 news articles from four Indonesian online news portals such as, The Jakarta Post, Tempo English, Republika, and Antara News published during the 2024 presidential election, this study addresses that gap. A 16-point instrument assessing source selection, lexical choices, framing techniques, and information balance was used to judge articles. Results show that 56% of articles showed pro-government bias, with an average score of 4.52/16. During pre-election and election month times, bias levels were much greater than those in the post-election period. Pro-government bias was purposely created by means of partisan evaluative language, calculated source quoted, and strategic headline framing. The manifestation and intensity of bias were determined by contextual variables like temporal proximity to the election, issue sensitivity, law enforcement climate, and media channel attributes. The research shows how English language Indonesian political news systematically creates ideological positioning using language and frame strategies, therefore helping to explain bias mechanisms more generally in non-Western, EFL media environments.

References

Ahmed, Y. (2021). Political discourse analysis: a decolonial approach. Critical Discourse Studies, 18(1), 139–155. https://doi.org/10.1080/17405904.2020.1755707

Amenah Hussein Ali. (2025). NAVIGATING NEUTRALITY: A LINGUISTIC ANALYSIS OF BIAS IN POLITICAL INTERPRETING. International Journal of Humanities and Educational Research, 07(01). https://doi.org/10.47832/2757-5403.30.11

Baly, R., Da San Martino, G., Glass, J., & Nakov, P. (2020). We Can Detect Your Bias: Predicting the Political Ideology of News Articles. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 4982–4991. https://doi.org/10.18653/v1/2020.emnlp-main.404

Chekalina, V., Razzhigaev, A., Sayapin, A., Frolov, E., & Panchenko, A. (2022). MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 355–365. https://doi.org/10.18653/v1/2022.acl-srw.27

Chen, R., & Liu, F. (2024). Deliberate ambiguity as motivated strategy. Language & Communication, 94, 1–12. https://doi.org/10.1016/j.langcom.2023.11.003

Chen, W., Pacheco, D., Yang, K. C., & Menczer, F. (2021). Neutral bots probe political bias on social media. Nature Communications, 12(1). https://doi.org/10.1038/s41467-021-25738-6

Creswell, J. W. & P. C. N. (2018). Qualitative Inquiry and Research Design: Choosing among Five Approaches (4th ed.). SAGE Publications.

Dezhkameh, A. , L. N. , & H. Y. (2021). A Critical Discourse Analysis of Covid-19 in Iranian and American Newspapers. GEMA Online® Journal of Language Studies, 21(3), 231–244. https://doi.org/10.17576/gema-2021-2103-13

Domingos de Arruda, G., Trevisan Roman, N., & Maria Monteiro, A. (2020). Analysing Bias in Political News.

Fairclough. (2013). Fairclough-Norman-Critical-Discourse-Analysis.-The-Critical-Study-of-Language.

Fairclough, N. (1995). Critical discourse analysis: The critical study of language. Longman.

Hamborg, F., Donnay, K., & Gipp, B. (2019). Automated identification of media bias in news articles: an interdisciplinary literature review. International Journal on Digital Libraries, 20(4), 391–415. https://doi.org/10.1007/s00799-018-0261-y

Imani, A. P., & Wahyudi, R. (2025). A critical discourse analysis of media political bias on Marvel’s Sabra controversy. Englisia : Journal of Language, Education, and Humanities, 12(2), 16. https://doi.org/10.22373/ej.v12i2.23446

Ismail Ahmad Simo, H., & Ali Ahmed, H. (2023). Bias in Translating Political Discourse. The Journal of University of Duhok, 26(1), 1122–1139. https://doi.org/10.26682/hjuod.2023.26.1.68

Kim, E., Lelkes, Y., & McCrain, J. (2022). Measuring dynamic media bias. Proceedings of the National Academy of Sciences, 119(32). https://doi.org/10.1073/pnas.2202197119

Klepka, R. (2019). MEDIA POLITICAL BIAS : IN SEARCH OF CONCEPTUALIZATION MEDIALNA STRONNICZOŚĆ POLITYCZNA: W POSZUKIWANIU KONCEPTUALIZACJI. 64(4), 155–168.

Lazaridou, K., & Krestel, R. (2016). Identifying Political Bias in News Articles.

Lestari, N. S., Adelina, Y. S., De Napoli Marpaung, F., Ginting, D. A., Id, N. A., Keguruan, S. T., Pendidikan, I., Maksum, A., & Utara, S. (2024). IDEAS Journal of Language Teaching and Learning, Linguistics and Literature A Critical Discourse Analysis of E-Paper 'KPU chief rebuffs allegations of bias during VP debate" in Jakarta Post. 12(1), 188–207. https://doi.org/10.24256/ideas

Morstatter, F., Wu, L., Yavanoglu, U., Corman, S. R., & Liu, H. (2018). Identifying Framing Bias in Online News. ACM Transactions on Social Computing, 1(2), 1–18. https://doi.org/10.1145/3204948

Ness, E., Fatima, A., & Oghaz, M. M. (2023). Data Driven Model to Investigate Political Bias in Mainstream Media. IEEE Access, 11, 41880–41893. https://doi.org/10.1109/ACCESS.2023.3270630

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y

Reddy, R. R., Duggenpudi, S. R., & Mamidi, R. (2019). Detecting Political Bias in News Articles Using Headline Attention. https://www.ethnologue.com/statistics/size

Rodrigo-Ginés, F. J., Carrillo-de-Albornoz, J., & Plaza, L. (2024). A systematic review on media bias detection: What is media bias, how it is expressed, and how to detect it. In Expert Systems with Applications (Vol. 237). Elsevier Ltd. https://doi.org/10.1016/j.eswa.2023.121641

Scheufele, D. A., & Iyengar, S. (2019). The State of Framing Research. In The Oxford Handbook of Political Communication (pp. 619–632). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199793471.013.47

Seinsiani, I. G., Urip, S. R., Yuniawan, T., Din, W. A., Swanto, S., & Ardi, H. (2023). Media Framing and COVID-19 Infodemic in News Headlines of Indonesian Online Newspapers. Eurasian Journal of Applied Linguistics, 9(2), 19–32. https://doi.org/10.32601/ejal.902003

Spinde, T., Rudnitckaia, L., Mitrović, J., Hamborg, F., Granitzer, M., Gipp, B., & Donnay, K. (2021). Automated identification of bias inducing words in news articles using linguistic and context-oriented features. Information Processing & Management, 58(3), 102505. https://doi.org/10.1016/j.ipm.2021.102505

Van Dijk, T. A. (2008). Discourse and Power. Palgrave Macmillan.

Yu, H., Lu, H., & Hu, J. (2021). A Corpus-Based Critical Discourse Analysis of News Reports on the COVID-19 Pandemic in China and the UK. International Journal of English Linguistics, 11(2), 36. https://doi.org/10.5539/ijel.v11n2p36

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Published

2026-02-26

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