This paper presents an approach to geolocating users of online social networks, based solely on their `friendship' connections. We observe that users interact more regularly with those closer to themselves and hypothesise that, in many cases, a person's social network is sufficient to reveal their location.
The geolocation problem is formulated as a classiffication task, where the most likely city for a user without an explicit location is chosen amongst the known locations of their social ties. Our method uses an SVM classiffier and a number of features that re
ect different aspects and characteristics of Twitter user networks.
The SVM classi er is trained and evaluated on a dataset of Twitter users with known locations. Our method outperforms a state-of-the-art method for geolocating users based on their social ties.