Geography of Twitter networks

We use a sample of publicly available data on Twitter to study networks of mostly weak asymmetric ties. We show that a substantial share of ties lie within the same metropolitan region. As we examine ties between regional clusters, we find that distance, national borders and the difference in languages all affect the pattern of ties. However, Twitter connections show the more substantial correlation with the network of airline flights, highlighting the importance of looking not just at distance but at pre-existing ties between places.