Are We Still Friends? Evaluating Tie Persistence in Mobility Traces

The advent of mobility networks brought to the surface the need to understand how mobile entities behave, specially considering how the interactions among them are affected. With the arrival of wireless and mobile networks such as 5G, the characterization of contacts between users becomes more and more important. Thereof, protocols, algorithms and applications started to lure on this kind of information. However, we still have to understand better how these interactions change over time and what are the factors that rule them. In this work, we analyze a mobility trace containing data about Wi-Fi users in a university campus over the period of one year to understand how time and space affect their relationships. To do so, we use a set of previously studied metrics to classify contacts between users into random and social. This classification is based on the number of contacts in common between two users and their encounter regularity, i.e., how frequently they meet during their routine. Additionally, this study contributes by going one step further and classifying users into those same categories according to their contacts distribution. Then, we consider how these users and contacts evolve over time, and what is the role of location and time in this evolution. Finally, we discuss how such evolution information can be used to provide better solutions in mobile networks, such as through the ability to predict how long a contact will last, or the ability to measure how qualified a certain user is to deliver a message.