Computational Social Networks: Mining and Visualization - Tapa blanda

Acerca del autor

Dr. Ajith Abraham is the Director of Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference on Computational Aspects of Social Networks (CASoN), Chair of the IEEE Systems Man and Cybernetics SocietyTechnical Committee on Soft Computing (since 2008), and Distinguished Lecturer for the IEEE Computer Society representing Europe (since 2011).

Dr. Aboul-Ella Hassanien is a Professor in the Faculty of Computers and Information at Cairo University, Egypt, and Visiting Professor at the College of Business Administration, Kuwait University."

De la contraportada

The study of computational social networks (CSNs) is an emerging interdisciplinary field, concerned with the intersection of social behavior and computer systems.

Due to the dynamic and ever-evolving nature of social networks, it can be difficult to comprehend the connections and influence between users. However, visualization techniques can aid the understanding of how these networks function. This comprehensive text/reference is the third of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on knowledge discovery and visualization of complex networks (the other two volumes review Tools, Perspectives, and Applications, and Security and Privacy in CSNs).

Topics and features:

• Includes a thorough introduction to this exciting and blossoming field
• Presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage from a better understanding of complex social networks
• Discusses the design and use of a wide range of computational tools and software for social network analysis
• Describes simulations of social networks, and the representation and analysis of social networks, highlighting methods for the data mining of CSNs
• Provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology

This authoritative work is a useful resource for researchers and developers involved in social network research and related issues. Postgraduate and senior undergraduate students will also find this a valuable reference for courses on CSNs.