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Springer Social Networks: A Framework of Computational Intelligence - 526

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Description

This comprehensive volume from Springer explores Computational Intelligence applied to social network analysis, synthesis, and evaluation. The book addresses critical topics including community structure detection, online social network dynamics, knowledge growth and evaluation, and diverse collaboration mechanisms. Written for researchers and practitioners, it integrates multiple Computational Intelligence methods with established techniques to provide both theoretical foundations and practical approaches to understanding complex social systems. The material is structured for in-depth learning and offers coherent coverage of how computational methods can solve real-world social network challenges. Part of the Studies in Computational Intelligence series (volume 526), this resource bridges the gap between abstract concepts and actionable insights for anyone working with network analysis, data science, or artificial intelligence applications in social contexts.

Key Features

Social Networks volume 526 from the Studies in Computational Intelligence series covers advanced computational methods for network analysis and evaluation.

Community structure detection methods enable identification of groups and clusters within complex social networks.

Online social networks section addresses modern platforms and real-time dynamics of digital social systems.

Knowledge growth and evaluation frameworks help measure how information spreads and evolves across connected systems.

Collaboration mechanism diversity is explored through multiple Computational Intelligence techniques and linear programming approaches.

Springer publication ensures peer-reviewed academic quality and reliability for advanced study and professional reference.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
19 December 2013
Listed Since
27 September 2013

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