Random walk mixing times reveal how users get trapped in algorithmic clusters. This research quantifies the mathematical probability of a user escaping a niche content bubble. By mapping these social graphs, the study identifies structural bottlenecks in discovery. Practitioners can use these metrics to audit recommendation engines for excessive echo-chamber effects.