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Temporal Patterns of Communication in Social Networks Springer Theses by Giovanna Miritello (auth.) is a nonfiction available to read on EtoBox.

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The main interest of this research has been in understanding and characterizing large networks of human interactions as continuously changing objects. In fact, although many real social networks are dynamic networks whose elements and properties continuously change over time, traditional approaches to social network analysis are essentially static, thus neglecting all temporal aspects. Specifically, we have investigated the role that temporal patterns of human interaction play in three main fields of social network analysis and data mining: characterization of time (or attention) allocation in social networks, prediction of link decay/persistence, and information spreading. In order to address this we analyzed large anonymized data sets of phone call communication traces over long periods of time. Access to these observations was granted by Telefonica Research, Spain. The findings that emerge from our research indicate that the observed heterogeneities and correlations of human temporal patterns of interaction significantly affect the traditional view of social networks, shifting from a very steady to a highly complex entity. Since structure and dynamics are tightly coupled, they c

Who reads Temporal Patterns of Communication in Social Networks Springer Theses?

Author

Giovanna Miritello (auth.)

Publisher

Springer International Publishing : Imprint : Springer

Published

2013

Language

EN

ISBN

9783319001098

Category

nonfiction

Subjects

Mathematics, Science, Sociology