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The study of social networks originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding.

General areas of interest to the book include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

More specialized topics within Social Network Analysis and Mining include, but are not limited to:
*       Anomaly detection in social network evolution
*       Application of social network analysis
*       Application of social network mining
*       Communities discovery and analysis in large scale online social networks
*       Communities discovery and analysis in large scale offline social networks
*       Connection between biological similarities and social network formulation
*       Contextual social network analysis
*       Contextual social network mining
*       Crime data mining and network analysis
*       Cyber anthropology
*       Dark Web
*       Data protection inside communities
*       Detection of communities by document analysis
*       Dynamics and evolution patterns of social networks
*       Economical impact of social network discovery
*       Evolution of patterns in the Web
*       Evolution of communities in the Web
*       Evolution of communities in organizations
*       Geography of social networks
*       Impact of social networks on recommendations systems
*       Information acquisition and establishment of social relations
*       Knowledge networks
*       Influence of cultural aspects on the formation of communities
*       Large-scale graph algorithms for social network analysis
*       Misbehavior detection in communities
*       Migration between communities
*       Multi-agent based social network modeling and analysis
*       Open source intelligence
*       Pattern presentation for end-users and experts
*       Personalization for search and for social interaction
*       Preparing data for Web mining
*       Political impact of social network discovery
*       Privacy, security and civil liberty issues
*       Recommendations for product purchase, information acquisition and establishment of social relations
*       Recommendation networks
*       Scalability of social networks
*       Scalability of Search algorithms on social networks
*       Social and cultural anthropology
*       Social geography
*       Social psychology of information diffusion
*       Temporal analysis on social networks topologies
*       Visual representation of dynamic social networks
*       Web mining algorithms
*       Web communities

Tentative deadlines
Papers reporting original and unpublished research results pertaining to the above topics are solicited. Full paper submission deadline is February 15, 2010. These papers will follow an academic review process. Full paper manuscripts must be in English with a maximum length of 20pages (using the LNCS template). Submissions should include the title, author(s), affiliation(s), e-mail address(es), tel/fax numbers, abstract, and postal address(es) on the first page. Papers should be submitted to Nasrullah Memon via email to [log in to unmask] by February 15, 2010. The attachment must be in PDF.

Papers will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation. Authors should certify that their papers represent substantially new previously unpublished work.  

Tansel Özyer
Department of Computer Engineering
TOBB ETU, Ankara Turkey
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