Structure and tie strengths in mobile communication networks

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Structure and tie strengths in mobile communication networks
J.-P. Onnela*, , J. Saramäki , J. Hyvönen , G. Szabó ,§, D. Lazer¶, K. Kaski , J. Kertész , A.-L. Barabási ,§
Physics Department, Clarendon Laboratory, Oxford University, Oxford, OX1 3PU, U.K.; Laboratory of Computational Engineering, Helsinki University of Technology, P.O.Box 9203, FI02015 TKK, Finland; Department of Physics andCenter for Complex Networks Research, University of Notre Dame, IN 46556, USA; §Center for Cancer Systems Biology, Dana Farber Cancer Institute, Harvard University, Boston, MA 02115, USA; ¶John F. Kennedy School of Government, Harvard University, Cambridge, MA 02138, USA; and Department of Theoretical Physics, Budapest University of Technology and Economics, H1111 Budapest, Hungary
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To whomcorrespondence should be addressed. E-mail:

Electronic databases, from phone to emails logs (1, 2, 3, 4), currently provide detailed records of human communication patterns, offering novel avenues to map and explore the structure of social and communication networks. Here we examine the communication patterns of millions of mobile phone users, allowing us tosimultaneously study the local and the global structure of a society-wide communication network. We observe a coupling between interaction strengths and the network’s local structure, with the counterintuitive consequence that social networks are robust to the removal of the strong ties, but fall apart following a phase transition if the weak ties are removed. We show that this coupling significantly slowsthe diffusion process, resulting in dynamic trapping of information in communities, and find that when it comes to information diffusion, weak and strong ties are both simultaneously ineffective.


Uncovering the structure and function of communication networks has always been constrained by the practical difficulty of mapping out interactions among a large number of individuals. Indeed,most of our current understanding of communication and social networks (5) is based on questionnaire data, reaching typically a few dozen individuals and relying on the individual’s opinion to reveal the nature and the strength of the ties. The fact that currently an increasing fraction of human interactions are recorded from email (1, 2, 3) to phone records (4), offers unprecedented opportunities touncover and explore the large scale characteristics of communication and social networks. Here we take a first step in this direction by exploiting the widespread use of mobile phones to construct a map of a societywide communication network, capturing the mobile interaction patterns of millions of individuals. The dataset allows us to explore the relationship between the topology of the networkand the tie strengths between individuals, information that was inaccessible at the societal level before. We demonstrate a local coupling between tie strengths and network topology, and show that this coupling has important consequences for the network’s global stability if ties are removed, as well as for the spread of news and ideas within the network. A significant portion of a country’scommunication network was reconstructed from 18 weeks of all mobile phone call records among approximately 20% of the country’s entire population, 90% of whose inhabitants had a mobile phone subscription (see Supporting Information). While a single call between two individuals during 18 weeks may not carry much information, reciprocal calls of long duration between two users serves as a signature ofsome work, family, leisure or service based relationship. Therefore, in order to translate the phone log data into a network representation that captures the characteristics of the underlying communication network, we connect two users with an undirected link if there has been at least one reciprocated pair of phone calls between them—i.e., A called B, and B called A— and define the strength, w AB...
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