Decoding Authenticity In Digital Marketing: A Netnographic Study Of User-Generated Content, Algorithmic Curation, And Brand Storytelling On @Scarlettofficial - Rofian Dedi Susanto; Rifky Maulana (Buana Komunikasi (Jurnal Penelitian dan Studi Ilmu Komunikasi), 2026)
This research explores the intersection of algorithmic curation and brand authenticity on Instagram, focusing on @scarlettofficial. In a digital landscape governed by engagement-driven algorithms, brands face a tension between high-fidelity production and consumer demand for unvarnished authenticity. Utilizing a netnographic approach (July–September 2025) and grounded theory analysis, this study investigates how the strategic deployment of low-fidelity User-Generated Content (UGC) serves as a structural bridge to bypass algorithmic gatekeeping. Findings reveal that @scarlettofficial navigates the "pseudo-individuality" trap by integrating raw, peer-driven visual assets into its marketing matrix. These low-fidelity markers—characterized by natural lighting and informal narratives—function as potent social proof, fostering deep discursive engagement that satisfies both algorithmic metrics and the psychological need for authenticity. This study contributes to digital communication theory by framing authenticity as a dynamic, algorithmically mediated social construction.