Call For Book Chapters


Social Networks: Computational Aspects and Mining


To be published  by  Springer   in  the Series  "Computer and Communication Networks"   -  2011

 Deadline for full chapter: 31 December, 2010

Submission Web site:

Volume Editor's : Ajith Abraham and  Aboul Ella Hassanien

Book Objectives: Mining social networks become  a very popular research area not only for data mining and web mining but also social network analysis. Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Recently, many data mining researches are focusing on developing new data mining techniques for social networks. However, it is meaningless, if the discovered valuable and useful data have not been applied in real application environment. Web 2.0 has enabled a new generation of Web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. Social network analysis is a rapidly growing field within the Web intelligence domain. The recent developments in Web 2.0 have provided more opportunities to investigate the dynamics and structure of Web-based social networks.  Recent trends also indicate the usage of social networks as a key feature for next generation usage and exploitation of the Web.   This book  provides an opportunity to compare and contrast the ethological approach to social behavior in animals (including the study of animal tracks and learning by members of the same species) with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks.  The main topics cover the design and use of various computational intelligence tools and software, simulations of social networks, representation and analysis of social networks, use of semantic networks in the design and community-based research issues such as knowledge discovery, privacy and protection, and visualization. In this book, we aim at gathering the latest advances of various topics in intelligence social networks and reporting how organizations can gain competitive advantages by applying the different emergent techniques in the real-world scenarios. Chapters and studies which couple the intelligence techniques and theories with specific networks technology problems are cordially invited. Survey articles that emphasize the research and application of intelligence  social networks in a particular domain are greatly welcome.The primary target audience for the book includes researchers, scholars, postgraduate students and developers who are interested in intelligence social networks research and related issues. The book will provide reviews of the cutting–edge technologies and insights for SN-based systems. In particular, the book will be valuable companion and comprehensive reference for both postgraduate and senior undergraduate students who are taking a course in Mining Social Networks. The book will be organized in self-contained chapters to provide greatest reading flexibility.


 Recommended topics include but are not limited to the following:



Submission Guidelines


- Each chapter must be self-contained and not exceed 30 pages,

- Please centralize all tables and figures with appropriate legends,

- Please carefully check for typos inside the text, figures, legends, etc.

- All equations must be numbered and please try to use standard fonts.

- Produce a LaTeX version of your chapter using the template provided in the Author Guidelines


Researchers and practitioners are kindly invited to submit Full chapters by December 31, 2010. All submitted chapters will be reviewed by at least three reviewers.

Submission site:

Important Dates

Deadline for chapter proposal (title  and abstract)

November 30, 2010

Deadline for chapter submission

December 31, 2010

Notification of acceptance/rejection of chapters 

Januray 31 2011

Deadline for submission of final chapters 

Febrary 28 2011

Publication of book:    

3-4 months

 Volume Editors


              Ajith Abraham

Machine Intelligence Research Labs (MIR Labs),

Scientific Network for Innovation and Research Excellence, USA




Aboul Ella Hassanien (Abo)

Faculty of Computer and Information, 

Information Technology Department,

Cairo University,

5 Ahmed Zewal St., Orman, Giza, Egypt