DIGITAL INFLUENCE AS AN ALGORITHMIC CONDITION: COMPUTATIONAL AUTHENTICITY, ALGORITHMIC ENTREPRENEURSHIP, AND DIGITAL VISIBILITY

Abstract

As platforms like Instagram shift from chronological feeds to algorithm-driven models, visibility is no longer an organic byproduct of social interactions but an ontological condition structured by opaque computational processes. Existing literature on digital influence—centered on authenticity, visibility management, and commercialization—fails to account for how platforms actively shape what is recognized as influential, valuable, or authentic. We demonstrate how algorithmic infrastructures rupture traditional influencer studies, exposing the limits of frameworks that conceptualize influence as human-centered. Instead, we propose that influencing the digital requires acting for, on behalf of, and through the digital itself. We introduce three interrelated modes to capture this transformation: computational authenticity, algorithmic entrepreneurship, and digital visibility. These categories illustrate how influencers must strategically engage with recommendation systems, optimize engagement metrics, and navigate platform affordances to maintain relevance. This study challenges human-centric models and highlights the structural conditions governing visibility by repositioning digital influence as an ontological entanglement between influencers, platforms, and algorithmic infrastructures. We argue that digital influence is not simply mediated by technology but co-produced by sociotechnical arrangements that define who and what gains recognition in algorithmic environments. This shift demands new conceptual tools to understand how influence is actively negotiated within digital infrastructures rather than merely performed for human audiences.