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Understanding Large Temporal Networks and Spatial Networks explores social mechanisms that drive network change and links them to computationally sound models of changing structure to detect patterns. The authors explore the social processes generating these networks and their evolution, while presenting a collection of large-scale network analyses with multiple emphasis on the development of network evolution theory and the development and exposition of visualization, pattern recognition, clustering, and simulation methods for network analysis. The authors consider the various types of units simultaneously involved in complex networks.

Key Features:

• Provides an overview of different approaches to studying large temporal networks and spatial networks.

• Contains multiple examples of networks including citations across Supreme Court cases, spatial linkage among US states, patent linkages, bibliometrics, and the structure of national scientific systems.

• Examines generative evolutionary networks and network mechanisms.

• Supported by downloadable datasets via a website link.

• Written by leaders in the field of temporal networks and spatial networks.

This book provides many useful insights for scientists involved with social network analysis, bibliometrics, cluster analysis, network visualization, computer science, and social sciences

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