Affiliations: [a] Grandata Labs, Buenos Aires, Argentina. E-mails: [email protected], [email protected], [email protected], [email protected] | [b] Department of Computer Science, Universidad de Buenos Aires, Buenos Aires, Argentina. E-mail: [email protected] | [c] Physics Department, Universidad de Buenos Aires, Buenos Aires, Argentina. E-mail: [email protected] | [d] Instituto de Cálculo, Universidad de Buenos Aires, Buenos Aires, Argentina | [e] CONICET, Buenos Aires, Argentina
Correspondence:
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Corresponding author: Carlos Sarraute, Grandata Labs, Buenos Aires, Argentina. E-mail: [email protected].
Abstract: The massive amounts of geolocation data collected from mobile phone records have sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are reflected in mobile phone data, providing some proof-of-principle examples. We illustrate in various ways how these events are reflected in the data, and show how information about the events can be used to improve predictability in a simple model for a mobile phone user’s location. We further propose a method for the automatic detection of such events and discuss their relation to the social fabric as derived from mobile phone communications.
Keywords: Human mobility, human predictability, social phenomena
