Social Networks: A Framework of Computational Intelligence

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes.

Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.

• Computational Intelligence
• Social Networks

From the book reviews:

“This interesting book is about social networks … and the many tools from the world of computational intelligence that provide a framework for analyzing and drawing conclusions from them. … I recommend this fascinating volume to practitioners, researchers, and students with an interest in any aspect of applying computational intelligence techniques and tools to extract insights from social networks.” (M. G. Murphy, Computing Reviews, July, 2014)

• Electrical & Computer Engineering, University of Alberta, Edmonton, Canada

  Witold Pedrycz

• Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

  Shyi-Ming Chen

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