Authors : Shreyas B. S.

Volume/Issue : Volume 11 - 2026, Issue 9 - September

Google Scholar : https://tinyurl.com/yck8vrh5

DOI : https://doi.org/10.38124/ijisrt/26sep336

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The present study examines the patterns of algorithmic amplification on social media space to deceive public opinions and preferences, known as political astroturfing—a process practiced by political parties, non-state actors and interest groups that fake grassroots support for and against a particular cause, in reality, a strategically orchestrated action. This study employs a single case study design within a fully qualitative research framework, conducting a fully manual thematic analysis of primary and secondary sources available in the public domain to understand the tactics used by camouflaged groups to disseminate manufactured content that circumvents digital infrastructure requirements and operates on behalf of hidden sponsors. This study identified a case from the Philippine presidential election, 2016, a digital campaign linked with Duterte in which a sponsored network of troll accounts disguised as genuine social media influences intruded on Facebook’s public interaction and engagement metrics to manufacture the advent of simulated grassroots support. The case was selected for its rare documented evidence and scholarship to seek clarity on the process and practice of astroturfing through algorithmic amplification. The data synthesis presented three interlinking themes: manufactured reality through strategically arranged account networks, synchronized sharing to amplify the message for greater reach, and governance gaps arising from the hegemony of digital platforms. Finally, the paper argues that algorithmic amplification aids political astroturfing in the context of reaching out to the target groups with a manufactured message. The study concludes with areas of future research.

Keywords : Algorithmic Amplification, Political Astroturfing, Social Media, Manufactured Reality, Synchronized Sharing.

References :

1. Bastos, M. T., & Mercea, D. (2017). The Brexit botnet and User-Generated Hyperpartisan news. Social Science Computer Review, 37(1), 38–54. https://doi.org/10.1177/0894439317734157
2. Bradshaw, S., & Howard, P. N. (2019). The Global Disinformation Order: 2019 Global Inventory of Organised Social Media Manipulation. Lincoln (University of Nebraska). https://digitalcommons.unl.edu/scholcom/207
3. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
4. BS, S. (2026). A study of specific cases to elucidate astroturfing techniques and policy outcomes. ShodhPatra: International Journal of Science and Humanities, 3(1), 131–135. https://doi.org/10.70558/spijsh.2026.v3.i1.45495
5. Cabañes, J. V. A. (2020). Digital disinformation and the imaginative dimension of communication. Journalism & Mass Communication Quarterly, 97(2), 435–452. https://doi.org/10.1177/1077699020913799
6. Company, F. (2021, March 24). Removing coordinated inauthentic behavior from the Philippines. Meta Newsroom. https://about.fb.com/news/2019/03/cib-from-the-philippines/
7. Computational propaganda. (2018). In Oxford University Press eBooks. https://doi.org/10.1093/oso/9780190931407.001.0001
8. Gorwa, R., & Guilbeault, D. (2018). Unpacking the social Media Bot: a typology to guide research and policy. Policy & Internet, 12(2), 225–248. https://doi.org/10.1002/poi3.184
9. Keller, F. B., Schoch, D., Stier, S., & Yang, J. (2019). Political astroturfing on Twitter: How to coordinate a disinformation campaign. Political Communication, 37(2), 256–280. https://doi.org/10.1080/10584609.2019.1661888
10. Kollanyi, B., Corvinus University, Howard, P. N., Oxford University, Woolley, S. C., & University of Washington. (2016). Bots and Automation over Twitter during the First U.S. Presidential Debate. https://regmedia.co.uk/2016/10/19/data-memo-first-presidential-debate.pdf
11. Krippendorff, K. (2019). Content Analysis: an Introduction to its methodology. https://doi.org/10.4135/9781071878781
12. Marwick, A. (2017). Media manipulation and disinformation online. https://doi.org/10.69985/qpaf6919
13. Ong, J. C., & Cabañes, J. V. A. (2019). Architects of Networked Disinformation: behind the scenes of troll accounts and fake news production in the Philippines. https://doi.org/10.7275/2cq4-5396
14. Propaganda war: Weaponizing the internet. (2016, October 3). Rappler. Retrieved August 17, 2026, from https://www.rappler.com/philippines/148007-propaganda-war-weaponizing-internet/
15. Tucker, J. A., Guess, A., Barbera, P., Vaccari, C., Siegel, A., Sanovich, S., Stukal, D., & Nyhan, B. (2018). Social Media, Political polarization, and Political Disinformation: A review of the Scientific literature. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3144139
16. Uyheng, J., & Carley, K. M. (2020). Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines. Journal of Computational Social Science, 3(2), 445–468. https://doi.org/10.1007/s42001-020-00087-4.