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In this paper we predict outgoing mobile phone calls using a machine learningapproach. We analyze to which extent the activity of mobile phone users ispredictable. The premise is that mobile phone users exhibit temporal regularityin their interactions with majority of their contacts. In the sociologicalcontext, most social interactions have fairly reliable temporal regularity. Ifwe quantify the extension of this behavior to interactions on mobile phones weexpect that caller-callee interaction is not merely a result of randomness,rather it exhibits a temporal pattern. To this end, we tested our approach onan anonymized mobile phone usage dataset collected specifically for analyzingtemporal patterns in mobile phone communication. The data consists of 783 usersand more than 12,000 caller-callee pairs. The results show that users' historiccalling patterns can predict future calls with reasonable accuracy.

On Temporal Regularity in Social Interactions: Predicting Mobile Phone Calls