title: The strength of friendship ties in proximity sensor data.
abstract: Understanding how people interact and socialize is important in many contexts from disease control to urban planning. Datasets that capture this specific aspect of human life have increased in size and availability over the last few years. We have yet to understand, however, to what extent such electronic datasets may serve as a valid proxy for real life social interactions. For an observational dataset, gathered using mobile phones, we analyze the problem of identifying transient and non-important links, as well as how to highlight important social interactions. Applying the Bluetooth signal strength parameter to distinguish between observations, we demonstrate that weak links, compared to strong links, have a lower probability of being observed at later times, while such links-on average-also have lower link-weights and probability of sharing an online friendship. Further, the role of link-strength is investigated in relation to social network properties.
authors.affiliation: Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Vedran
authors.initials: V
authors.lastname: Sekara
authors.affiliation: Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark; Niels Bohr Institute, University of Copenhagen, Østerbro, Denmark.
authors.forename: Sune
authors.initials: S
authors.lastname: Lehmann
mesh_terms: D033062:Friends / Q000523:psychology*; D006801:Humans; D007398:Interpersonal Relations; D011336:Probability; D061108:Social Media; D060756:Social Networking; D059015:Wireless Technology / Q000295:instrumentation*