In events such as natural disasters, terrorist attacks, or war zones, one can gain critical situational awareness by monitoring what people on the ground are saying in social media. But how does one build a set of users in a specific location from scratch? In “Building a Location-Based Set of Social Media Users,” Christopher Marks and Tauhid Zaman present an algorithm to do just this. The algorithm starts with a small set of seed users in the location and then grows this set using an “expand–classify” approach. They apply the algorithm to diverse regions ranging from South America to the Philippines and in a few hours can collect tens of thousands of Twitter users in the target locations. The algorithm is language agnostic, making it especially useful for anyone trying to gain situational awareness in foreign countries.