Algorithmic Affectography: An Onto-Aesthetic Framework for Understanding Visual Transformations in the Era of Digital Platforms

This paper proposes a new theoretical framework for understanding the aesthetic shifts in digital media: algorithmic affectography, which is defined as the aesthetic emerging from the affective resonance between users, algorithms, and the platform ecosystem. By integrating posthuman philosophy (Hayles, Braidotti), affect theory (Massumi, Paasonen), and new media theory (Manovich, Shaviro), this research argues that vertical video (9:16) is not a representation of aesthetic degradation, but an evolution towards a new paradigm: from representational aesthetics to affective-participatory aesthetics. Through a qualitative- quantitative analysis of 50 viral videos (2024–2025) from TikTok, Instagram Reels, and YouTube Shorts, the findings demonstrate three fundamental transformations: (1) a shift from formal composition to emotional resonance; (2) mass participation as an aesthetic mechanism; and (3) the algorithm as a posthuman curator. This paper contributes to contemporary discussions on post-cinematic aesthetics by offering the concept of affectography as an analytical and practical framework for academics, content creators, and platform designers.