Netizen Opinion on Corruption News in Social Media: Sentiment and Issue Framing in Indonesia

Authors

  • Hastuti Department of Communication Science, Faculty of Social and Political Sciences, Universitas Muhammadiyah Buton, Baubau, Indonesia., Indonesia
  • Muhammad Iqbal Sultan Department of Communication Science, Faculty of Social and Political Sciences, Universitas Hasanuddin, Makassar, Indonesia., Indonesia
  • Syamsuddin Aziz Department of Communication Science, Faculty of Social and Political Sciences, Universitas Hasanuddin, Makassar, Indonesia., Indonesia

DOI:

https://doi.org/10.30863/palakka.v7i1.11602

Keywords:

Corruption discourse, netizen opinion, digital public sphere, content analysis, journalism

Abstract

This study examines netizen opinion on corruption-related news in Indonesian social media, focusing on how sentiment, issue framing, and engagement patterns shape digital public discourse. The research aims to analyze how users respond to corruption narratives and to identify dominant patterns of opinion expression in online environments. Using a quantitative content analysis approach combined with computational sentiment analysis, the study analyzes 149 social media mentions collected through an automated analytics platform. The methodology integrates sentiment classification, keyword mapping, and engagement metrics to provide a comprehensive understanding of discourse dynamics. The results indicate that negative sentiment dominates the discourse, accounting for more than half of the total mentions, followed by neutral and positive sentiments. Keyword analysis reveals that discussions are primarily framed around legal and economic issues, including prosecution processes, state financial losses, and institutional accountability. Engagement patterns show that emotionally charged content, particularly negative narratives, tends to generate higher levels of interaction across platforms such as Instagram and TikTok. These findings suggest that social media functions as a hybrid public sphere where informational and affective elements interact to shape public opinion. The study highlights the importance of digital platforms in influencing public perceptions of corruption and institutional trust. By combining computational analysis with theoretical insights, this research contributes to a deeper understanding of digital public opinion formation and offers implications for media, policymakers, and scholars interested in corruption communication.

References

Babac, M. B., & Podobnik, V. (2018). What Social Media Activities Reveal About Election Results? The Use of Facebook During the 2015 General Election Campaign in Croatia. Information Technology and People, 31(2), 327–347. https://doi.org/10.1108/itp-08-2016-0200

Bogoch, B., & Holzman‐Gazit, Y. (2008). Mutual Bonds: Media Frames and the Israeli High Court of Justice. Law & Social Inquiry, 33(1), 53–87. https://doi.org/10.1111/j.1747-4469.2008.00094.x

Echeverría, M., & Mani, E. (2020). Effects of Traditional and Social Media on Political Trust. Communication & Society, 119–135. https://doi.org/10.15581/003.33.2.119-135

Figueiras, R., Santo, P. E., & Cunha, I. F. (2014). Democracy at Work: Pressure and Propaganda Pressure and Propaganda in Portugal and Brazil. https://doi.org/10.14195/978-989-26-0917-1

Jackson, S. (2024). A New Transformation of the Public Sphere? Questions on Identity, Power, and Affect. INTERNATIONAL JOURNAL OF COMMUNICATION, 18, 4662–4665. (WOS:001354504300007).

Marchal, N. (2021). “Be Nice or Leave Me Alone”: An Intergroup Perspective on Affective Polarization in Online Political Discussions. Communication Research, 49(3), 376–398. https://doi.org/10.1177/00936502211042516

Marichal, J., & Neve, R. (2019). Antagonistic Bias: Developing a Typology of Agonistic Talk on Twitter Using Gun Control Networks. Online Information Review, 44(2), 343–363. https://doi.org/10.1108/oir-11-2018-0338

McNutt, M. (2018). Social TV fandom and the media industries. Transformative Works and Cultures, 26. https://doi.org/10.3983/twc.2018.1504

Milhazes-Cunha, J., & Oliveira, L. (2023). Doctors for the Truth: Echo Chambers of Disinformation, Hate Speech, and Authority Bias on Social Media. Societies, 13(10), 226. https://doi.org/10.3390/soc13100226

Miskolci, R., & Balieiro, F. d. F. (2023). The Moralization of Politics in Brazil. International Sociology, 38(4), 480–496. https://doi.org/10.1177/02685809231180879

Pérez, C. R., Rojano, F. J. P., & Rosa, R. M. (2021). Debunking Political Disinformation Through Journalists’ Perceptions: An Analysis of Colombia’s Fact-Checking News Practices. Media and Communication, 9(1), 264–275. https://doi.org/10.17645/mac.v9i1.3374

Rambocas, M., & Pacheco, B. G. (2018). Online Sentiment Analysis in Marketing Research: A Review. Journal of Research in Interactive Marketing, 12(2), 146–163. https://doi.org/10.1108/jrim-05-2017-0030

Rossini, P. (2020). Beyond Incivility: Understanding Patterns of Uncivil and Intolerant Discourse in Online Political Talk. Communication Research, 49(3), 399–425. https://doi.org/10.1177/0093650220921314

Salam-Salmaoui, R., & Salam, S. (2023). Twitter and Politics: A Framing Analysis of Maryam Nawaz and Imran Khan’s Social Media Discourse. Frontiers in Communication, 8. https://doi.org/10.3389/fcomm.2023.1276639

Sampedro, V., López-Ferrández, F. J., & Carretero, Á. (2018). Leaks-Based Journalism and Media Scandals: From Official Sources to the Networked Fourth Estate? European Journal of Communication, 33(3), 255–270. https://doi.org/10.1177/0267323118763907

Wang, Y., & Fikis, D. J. (2017). Common Core State Standards on Twitter: Public Sentiment and Opinion Leaders. Educational Policy, 33(4), 650–683. https://doi.org/10.1177/0895904817723739

Zhang, C., Gupta, A., Sun, H., Li, Y., & Qin, X. (2022). RT-FEND: Spark-Based Real Time FakE News Detection. IEEE Int. Conf. Netw., Archit. Storage, NAS - Proc. Scopus. 2022 IEEE International Conference on Networking, Architecture and Storage, NAS 2022 - Proceedings. https://doi.org/10.1109/NAS55553.2022.9925512

Zhang, G., Li, Q., Gao, M., Guo, S., Jeon, G., & Abdelmoniem, A. M. (2025). Space-Frequency and Global-Local Attentive Networks for Sequential Deepfake Detection. IEEE Transactions on Computational Social Systems. Scopus. https://doi.org/10.1109/TCSS.2025.3541346

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Published

2026-06-29

How to Cite

Hastuti, Muhammad Iqbal Sultan, & Syamsuddin Aziz. (2026). Netizen Opinion on Corruption News in Social Media: Sentiment and Issue Framing in Indonesia. Palakka : Media and Islamic Communication, 7(1), 62–76. https://doi.org/10.30863/palakka.v7i1.11602

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