Exploring Algorithmic Cultivation – Sensitive Self-Disclosure, Self-Diagnosis, and Hazardous Mental Health Communication on TikTok

Abstract: TikTok’s algorithm (the “For You Page”) leads like-minded, like-diagnosed users together. Amid users frequenting comment sections, seldom research examines how venues of algorithmically-dominated social media might contextualize mental illness discourse. In exploration of how users’ perceived realities both inform and are informed by algorithmic social media environments, the present study offers a theoretical extension of cultivation theory. A reflexive thematic analysis of TikTok comment sections from 15 videos ( N = 15,540 comments) spanning mental illness-related topics including suicidality, bipolar disorder, eating disorders, premenstrual dysphoric disorder, and obsessive-compulsive disorder, positions shared and distinguished knowledge between subject groups as a central component of health communication on the platform. Findings illuminate processes of self-diagnosing, presence of an “algorithmic clock,” emotional contagion, and confession hour, driven by the algorithmic environment. Questioning healthcare treatment, looming stigma, and distinct relational struggles thematically illuminated the sharing of such illness-related experiences.