This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena.

Network theory has proven, over the past 20 years to be one of the most powerful tools for the study and analysis of complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the "big data" sets. This monograph will appeal to students, researchers and professionals alike interested in theory and temporal networks, a field that has grown tremendously over the last decade.

First contributed volume on the theory of temporal networks

Covers all trending theoretical topics

Contributions gathered from the top international researchers in the field

Autorentext

Petter Holme is a specially appointed professor at Tokyo Institute of Technology. His research interests cover many aspects of network science from data science to theory. He has about 150 scientific publications including about 30 on temporal networks. Jari Saramäki is a full professor of computational science at Aalto University, Finland. His research focuses on complex systems and networks, with applications ranging from computational social science to network neuroscience and biomedicine.

Inhalt

Modeling frameworks and tools.- 24 ways of thinking about your temporal network data.- Density and related concepts for discrete, directed, and/or weighted stream graphs.- Dynamics and control of stochastically switching networks: Beyond fast switching.- Visualisation of structure and processes on temporal networks.- Mapping sequences of events in temporal networks onto weighted event graphs.- Measures of temporal network structure.- Eigenvector-based centralities for temporal networks: Supracentralities with directed interlayer coupling.- Temporal graph metrics for temporal text networks.- Characterization of correlated bursts for temporal networks.- Mesoscopic structures.- Challenges in community discovery on temporal networks.- Fundamental structures in dynamic social networks.- Mapping and modelling sequences and temporal networks with dynamic community structures.- Epidemic spreading.- Spreading of infection on temporal networks: an edge-centered perspective.- The effect of concurrency on epidemic threshold in time-varying networks.- Epidemic thresholds on continuous-time evolving networks.- Other dynamic processes.- Reachability and concurrency in temporal networks.- The effects of local and global links creation mechanisms on spreading processes.- Information diffusion backbones.- Influence maximization in temporal networks.- Random walks on temporal networks.