Examining the Patterns of Algorithmic Amplification in the Context of Political Astroturfing

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.