The first generation of the World Wide Web has been characterized by the interaction between the user and the medium: Web sites offer information and services; new applications and even new business models emerged for institutions that offer a better information search experience, more well-informed purchase decisions and, more recently, for the sharing and the collaborative treatment of content. The next generation of the Web is reflected in the proliferating platforms for sharing and collaboration and in the design of Web 2.0, which is proactively oriented towards social activities in the Web.
The social flair of the Web poses new challenges for the data mining community. Social networking in the Web is a phenomenon of scientific interest per se; there is demand for flexible and robust community discovery technologies but also for interdisciplinary research on the rules and behavioral patterns that emerge and characterize community formation and evolution. Further, the social Web poses challenges for the individual; assistance and ultimately, personalization broad scope of activities, including the traditional search for documents, the less traditional search for multimedia content and the search for similar people and for answers to poorly articulated information needs. Moreover, the misuse potential of social formations cannot be stressed enough: People are confronted with unreliable or even malicious content, with surveillance and even stealth of information and of personal data; detection and protection mechanisms are needed here, based on a deep understanding of patterns of misuse and misbehavior. Finally, the diversity of social structures in the Web must be kept in mind: Social structures in the Web take many forms, including wikis and folksonomies where people contribute semantically rich content, platforms for collaborative annotations where people enrich existing content, bulletin boards and similar fora where people seek for advice but also establish new contacts, but also the implicit communities to be found in auction platforms and among the reviewers of products and services; these are communities where reputation and trust play a mission-critical role. Data miners are expected to deliver solutions for the challenges in searching, personalizing, understanding and protecting those social structures.
In addition to online communities, this joint workshop will also invite submissions on generic social network systems, including social network modeling, growth and evolution dynamics of social networks, graph-related algorithms, multi-agent based social network simulation, trend prediction of social network evolution, and applications in related domains.
The joint workshop of WEBKDD and SNA-KDD '2007 aims to bring together practitioners and researchers with a specific focus on the emerging trends and industry needs associated with the traditional Web, the social Web, and other forms of social networking systems. This includes (1) data mining advances on the discovery and analysis of communities, on personalization for solitary activities (like search) and social activities (like discovery of potential friends), on the analysis of user behavior in open fora (like conventional sites, blogs and fora) and in commercial platforms (like e-auctions) and on the associated security and privacy-preservation challenges; (2) social network modeling, scalable, customizable social network infrastructure construction , dynamic growth and evolution patterns identification and discovery using machine learning approaches or multi-agent based simulation.