Random walk mixing times reveal how users get trapped in ideological clusters on social platforms. This research quantifies the mathematical probability of a user escaping a specific content bubble. It provides a formal framework for understanding algorithmic isolation. Developers can use these metrics to tune recommendation engines for better information diversity.