Random-walk Based Sampling in Social Networks

Talk Abstract: How many friends do social network members have on average? What is a proportion of a certain sub-population in a social network? Are online social network users more likely to form friendships with those with similar attributes? Such questions frequently arise in the context of social network analysis, but often crawling an online social network via its application programming interface and conducting surveys in offline social networks are resource consuming and are prone to errors. Using regenerative properties of the random walks, we describe estimation techniques based on short crawls that have proven statistical guarantees. Moreover, these techniques can be implemented in low-complexity distributed algorithms.