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.
表中的内容
Modeling Frameworks and Tools.- Measures of Temporal Network Structure.- Mesoscopic Structures.- Epidemic Spreading.- Other Dynamic Processes.
关于作者
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.
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