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ASONAM 2010 : The 2010 International Conference on Advances in Social Networks Analysis and Mining

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Conference Series : Advances in Social Networks Analysis and Mining
 
Link: http://asonam2010.hau.gr/
 
When Aug 9, 2010 - Aug 11, 2010
Where Odense, Denmark
Submission Deadline Mar 15, 2010
Notification Due May 1, 2010
Final Version Due May 20, 2010
Categories    social networks   SNA   social web   social mining
 

Call For Papers

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.

The international conference on Advances in Social Network Analysis and Mining (ASONAM 2010) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. ASONAM 2010 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoretical works on social network analysis and mining along with their application to real life situations.

General areas of interest to ASONAM 2010 include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.

More specialized topics within ASONAM 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

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