Deepfake as algorithmic political culture: Negotiating communicative trust, authenticity, power, and public meaning during Indonesia's 2025 demonstrations

Abstract

The rapid advancement of generative artificial intelligence has transformed the landscape of political communication by challenging the authenticity and credibility of visual evidence during public protests. Indonesia's 2025 national demonstrations provide a strategic empirical context for examining this transformation within the Global South. Although previous studies have primarily examined deepfakes as a form of disinformation, limited attention has been given to how they constitute an algorithmic political culture through communicative processes. This study aims to develop a substantive theory of algorithmic political culture using a Constructivist Grounded Theory approach. Data were collected through in-depth interviews, digital observation, and document analysis until theoretical saturation was achieved. The analysis was informed by Critical Intercultural Communication, Deep Mediatization, and Platform Society as sensitizing concepts. The findings identify four interconnected communicative processes: Authenticity Disruption, Communicative Trust Negotiation, Algorithmic Meaning Amplification, and Collective Political Meaning Construction. These processes are integrated into the Algorithmic Political Culture Model (APCM), which explains that algorithmic political culture emerges through the co-constitutive interaction of synthetic media, platform algorithms, and citizens' communicative practices. The proposed model extends digital political communication theory by demonstrating how generative AI reshapes communicative trust, authenticity, and collective political meaning within the democratic contexts of the Global South.