Ubiquitous Social Networks: Opportunities and Challenges for Privacy-Aware User Modelling

Privacy has been recognized as an important topic in the Internet for a long time, and technological developments in the area of privacy tools are ongoing. However, their focus was mainly on the individual. With the proliferation of social network sites, it has become more evident that the problem of privacy is not bounded by the perimeters of individuals but also by the privacy needs of their social networks. The objective of this paper is to contribute to the discussion about privacy in social network sites, a topic which we consider to be severely under-researched. We propose a framework for analyzing privacy requirements and for analyzing privacy-related data. We outline a combination of requirements analysis, conflict-resolution techniques, and a P3P extension that can contribute to privacy within such sites.World Wide Web, privacy, social network analysis, requirements analysis, privacy negotiation, ubiquity, P3P

Semantic Network Analysis of Ontologies

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size

Preface

Recently, collaborative work and social networks came to the fore in many computer science areas. This shows up in the rise of research topics like communities of practice, knowledge management, web communities, and peer to peer. In particular the notion of communities- and thus the need of their systematic analysis- becomes more and more important. On the other hand, techniques for analysing such structures have a long tradition within sociology. While in the beginning, researchers in that area had to spent huge efforts in collecting data, they nowadays harvest the data free from the WWW. Popular examples are citation and co-author graphs, friend of a friend etc. A new kind of user-centered applications such as blogs, folksonomies, and wikis, now known as ”Web 2.0”, consist of large networks of individual contributions, providing a testbed for Social Network Analysis (SNA) techniques at the intersection of the semantic web and SNA areas. The semantic web provides an additional aspect to SNA on the Web as it distinguishes between different kinds of relations, allowing for more complex analysis schemes

08391 Group Summary -- The Evolution and Dynamics of Research Networks

Existing collaboration and innovation in scientific communities can be enhanced by understanding the underlying patterns und hidden relations. Social network analysis is an appropriate method to reveal such patterns. Nevertheless, research in this area is mainly focused on social networks. One promising approach is to use homophily networks as well. Furthermore, extending the static to a dynamic network model enables to understand existing interdependencies in these networks. A mathematical description of possible analyses is given. Finally, resulting research questions are illustrated and the necessity of an interdisciplinary research approach is pointed out