Content creators operating on video-sharing platforms like YouTube are subject to opaque, highly complex recommendation algorithms that dictate cultural visibility and financial viability. To survive, creators increasingly adopt rigorous search engine optimization (SEO) and algorithmic compliance strategies. However, this hyper-optimization generates a critical tension: the Optimization Paradox. As creators modify their behavioral and creative outputs to satisfy algorithmic objective functions (such as Click-Through Rate and Average View Duration), they risk eroding the parasocial trust, "messiness," and perceived authenticity that originally fostered their audience communities. This mixed-methods study (N=500 channels; 50 qualitative interviews) investigates the threshold at which algorithmic compliance becomes detrimental to long-term creator sustainability. We introduce the Authenticity-Optimization Matrix, a theoretical framework demonstrating an inverted U-curve relationship between algorithmic compliance and audience trust. Findings indicate that while baseline metadata optimization is necessary for initial discovery, over-optimization—characterized by algorithmic homogenization and AI-driven content sanitization—triggers audience backlash and long-term engagement decay. The paper concludes by proposing engineering and strategic frameworks to help creators balance data-driven growth with human-centric authenticity, redefining success in the creator economy beyond immediate platform metrics.
Daniel Whitmore (Mon,) studied this question.