The rapid expansion of digital media has fundamentally transformed the production, circulation, and authority of Qur’anic interpretation across the Muslim world. Whereas classical tafsir traditions grounded religious authority in scholarly sanad, linguistic expertise, and institutional recognition, contemporary digital platforms increasingly mediate religious meaning through algorithms, popularity metrics, and visual performance. Despite the growing scholarship on digital religion, empirical studies that critically examine how Qur’anic interpretation itself is reshaped by platform logics and how this process reconfigures religious authority remain limited, particularly in non-Western Muslim contexts. Addressing this gap, this study examines digital Qur’anic interpretation in Indonesia through a qualitative–quantitative content analysis of 50 tafsir-related contents collected from YouTube, TikTok, Instagram, Twitter/X, and digital tafsir websites. Drawing on theories of digital religion, mediated religious authority, and algorithmic governance, the analysis maps content formats, producer typologies, ideological strategies, and emerging forms of digital piety. The findings demonstrate that digital Qur’anic interpretation is dominated by short, motivational, and emotionally driven content aligned with the logic of social media virality. Religious authority is increasingly negotiated through visibility, aesthetic performance, and audience engagement rather than through classical scholarly credentials. The study also identifies distinct forms of digital piety—performative, communal, consumerist, ritual-digital, and emotional—reinforced by algorithmic mechanisms such as polarization, confirmation bias, and echo chambers of belief. Theoretically, this study conceptualizes a shift in Qur’anic interpretive authority from sanad-based legitimacy toward algorithmically mediated authority, while empirically positioning Indonesia as a critical case for understanding the global transformation of Qur’anic interpretation in the age of algorithms.
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