TY  - BOOK
AU  - Holme,Petter
AU  - Saramäki,Jari
TI  - Temporal networks
T2  - Springer complexity
SN  - 9783642364600
U1  - 003 20
PY  - 2013///
CY  - Heidelberg (Baden-Wurtemberg, Alemania)
PB  - Springer
KW  - Análisis de sistemas
KW  - Complejidad computacional
N1  - Incluye referencias bibliográficas; Temporal Networks as a Modeling Framework; Petter Holme, Jari Saramäki; Graph Metrics for Temporal Networks; Vincenzo Nicosia, John Tang, Cecilia Mascolo, Mirco Musolesi; Burstiness: Measures, Models, and Dynamic Consequences; Byungjoon Min, K.-I. Goh; Temporal Scale of Dynamic Networks; Rajmonda Sulo Caceres, Tanya Berger-Wolf; Models, Entropy and Information of Temporal Social Networks; Kun Zhao, Márton Karsai, Ginestra Bianconi; Temporal Motifs; Lauri Kovanen, Márton Karsai, Kimmo Kaski, János Kertész; Applications of Temporal Graph Metrics to Real-World Networks; John Tang, Ilias Leontiadis, Salvatore Scellato, Vincenzo Nicosia; Spreading Dynamics Following Bursty Activity Patterns; Alexei Vazquez; Time Allocation in Social Networks: Correlation Between Social Structure and Human Communication Dynamics; Giovanna Miritello, Rubén Lara, Esteban Moro; Temporal Networks of Face-to-Face Human Interactions; Alain Barrat, Ciro Cattuto; Social Insects: A Model System for Network Dynamics; Daniel Charbonneau, Benjamin Blonder, Anna Dornhaus; Self-Exciting Point Process Modeling of Conversation Event Sequences; Naoki Masuda, Taro Takaguchi, Nobuo Sato, Kazuo Yano; Infering and Calibrating Triadic Closure in a Dynamic Network; Alexander V. Mantzaris, Desmond J. Higham; Dynamic Communicability Predicts Infectiousness; Alexander V. Mantzaris, Desmond J. Higham; Random Walks on Stochastic Temporal Networks; Till Hoffmann, Mason A. Porter, Renaud Lambiotte; A Temporal Network Version of Watts's Cascade Model; Fariba Karimi, Petter Holme; Timing Interactions in Social Simulations: The Voter Model; Juan Fernández-Gracia, Víctor M. Eguíluz, Maxi San Miguel
N2  - The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and conceptually more challenging. This book is intended as a first introduction and state-of-the art overview of this rapidly emerging field
ER  -