Random walk mixing times reveal how users get trapped in algorithmic clusters. This research examines the mathematical structure of social media "rabbit holes" to quantify information isolation. By modeling user navigation as a stochastic process, the study identifies specific network bottlenecks. Practitioners can use these metrics to audit recommendation engines for echo chamber effects.