The research groups are as following:
- Knowledge Discovery & Text Mining
- Knowledge Visualization & Visual Analytics
- Knowledge Evolution & Social Semantic Web
- Knowledge Context & Sensors
- Game-based Learning
- Knowledge Space Theory
- Competence Maintenance
Network-Theory & Web Science
- Social Network Analysis
- Web Science
Recently, Network Science has emerged as a new multidisciplinary research field from various traditional fields such as computer science, physics, social science, or information theory. Researches from various fields recognized the nessecity to investigate not only properties of individuals but also their connections with other individuals. For example, the famous “Six Degrees of Separation” phenomenon from social sciences can be only explained by the existence of specific structural properties of social networks. Yet another example involves e.g. the success and growth of technologies such as the Internet or the Web. Th enormous growth of these technologies can be easily explained by simple dynamic properties (e.g. preferential attachment) of the network representations of the Internet and the Web.
In our group we investigate and analyze important questions in modern information and (online) social networks. In particular, we investigate e.g. the emergence of semantic relations in social tagging systems such as Delicious dependent on how these systems are used; information retrieval capabilites, in particular navigability, of various social media systems such as CiteULike or Mendeley; diffusion of diverse properties such as influence, or trust in online social networks such as Twitter; the emergance of abstract concepts and hierarchical organization of those concepts in systems such as Wikipedia; user behavior such as user search and navigation in social media.
The results of our research are of interest in diverse application areas such as knowledge engineering, software engineering, information systems and retrieval, social media, user modelling, or collaborative systems.