International Conference on Computational Aspects of Social Networks (CASoN 2009)
June 24 – 27, 2009, Fontainebleau, France

Conference Objective:
Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Recent trends also indicate the usage of complex network as a key feature for next generation usage and exploitation of the Web. This international conference on “Computational Aspect of Networks” is focused on the foundations of social networks as well as case studies, empirical, and other methodological works related to the computational tools for the automatic discovery of Web-based social networks. This conference 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.

The papers can be theoretical, practical and application oriented on the following themes (but not limited to):

* Network evolution
o Network evolution and growth mechanisms.
o Online communities and computer networks.
o Information diffusion in social networks.
o Detection of communities by document analysis.
o Topology of real networks.
* Recommendation
o Information diffusion in social networks.
o Recommendations for product purchase, information acquisition and establishment of social relations
o Impact of recommendation models on the evolution of the social network.
o Classification models and their application in social recommender systems.
* Advertisement models
o Economical impact of social network discovery
o Social advertising.
o Use of social networks for marketing.
* Search in network
o Web page ranking informed by social media.
o Search algorithms on social networks.
o Collaborative Filtering.
* Security
o Anomaly detection in social network evolution.
o Data protection inside communities.
o Crime data mining and network analysis.
o Modeling trust and reputation in social networks
o Misbehavior detection in communities
* Network geography
o Geographical clusters, networks, and innovation.
o Social geography.
o International Collaborations in e-Social network
* Web
o Automatic discovery and analysis of Web based social networks
o Link Topology and Site Hierarchy.
o Web mining algorithms.
o Web communities
o Web-Based Cooperative Work