Random walks are instrumental to network analysis. It provides theoretical foundation of community detection, centrality analysis, routing, and embedding.
Random walks in a simplest form
A simplest form is random walks in undirected and unweighted networks. An agent called a walker at a node and moves to node randomly chosen from the neighbors of node . This process is a markov process of the first order, i.e., the walker determines the next node based on the current node and has no memory of nodes previously visited.