Web Science
Web Science is a new, interdisciplinary scientific paradigm (or even discipline) that seeks to understand the Web in its whole with a focus on technical and social challenges. The term Web Science was coined by Berners-Lee and colleagues (2006) in a short Science article. Since than many researchers adopted the paradigm, organized specialized Web Science conferences and developed the paradigm further (e.g. Hendler et al. 2008). With our research we intend to foster the interdisciplinary discourse between scholars developing the Web and scholars examining the increasing amount of networked data in a variety of disciplines such as Information Systems, Computer science, Sociology, Physics, Management Science, Economics, Anthropology and Communication Studies.
Social Network Analysis
The term social network denotes the social structure that emerges from human actors' interaction with each other. Over the years, scholars in the domain of anthropology, sociology, psychology and organizational theory have proposed different methods and techniques to discover these structures and to allow inferences about functioning of social networks.
These methods and techniques are generally summarized under the term social network analysis.
The rise of web 2.0 and social networking sites in the internet have recently fostered various trends in scientific research about social networks. For example, sociological researchers, who have traditionally been dealing with SNA, started relying on methods from computer science to handle large amounts of electronically stored data, and IS and management scholars called their attention to SNA research and started integrating their own methods of data collection and analysi
Peer-to-Peer (P2P)
Reduced to a common denominator the term Peer-to-Peer (P2P) refers to technology which enables two or more peers to collaborate spontaneously in a network of equals (peers) by using appropriate information and communication systems without the necessity for central coordination.
Scientists and practitioners are confronted with the question whether, and if so, to what extent, P2P offers advantages in contrast to other architectural concepts, such as the client/server model. While comparisons on the basis of technical and economic criteria, such as persistence, performance or costs, can be made, they miss the point. Operating largely independent of central coordination, P2P opens up new dimensions of information management. It has the potential for accelerating communication processes, exploiting idle resources, and facilitating the exchange of the most recently created and highly distributed information. It can reduce collaboration costs through lean and ad hoc administration of working groups, even if groups extend beyond the boundaries of a company. They permit a greater degree of freedom and independence on the part of users by making resources available in a more customized manner. These benefits are strengthened by the increasing availability of powerful communication networks, a growing number of agreed technical standards for interfaces and protocols, as well as more user-friendly clients which make P2P architectures transparent for the user. It appears profitable to build information systems based on P2P architectures. However, the extent to which companies can take advantage of P2P is under debate. Will decentralized control be able to cope with challenges regarding network control, security, interoperability, meta data, and cost sharing?
Our topics of interest include:
- Web mining for purposes of (collective) trend prediction / collective intelligence / prediction markets / link prediction / agenda setting
- Social media (e.g. blogs, media sharing sites, opinion aggregators, Massively Multiplayer Online Games, social bookmarking sites and folksonomies, social networking platforms
- Diffusion processes (e.g. eWOM, viral marketing, identifying influentials)
- Decision Support Systems using the Web
- Theoretical properties of social machines in the Web
- Algorithms for creating social machines in the Web and analyzing social networks
- Architectural principles of a Web infrastructure for social software
- Cultural differences and social mechanisms on the Web
- Collaborative innovation networks (COINS) / virtual communication and collaboration
- Random graphs, modeling and simulation, or other approaches to empirical network analysis
- Trust, privacy, risk, transparency and security
- Promoting the paradigm of Web Science (e.g. curricular and epistemological underpinnings)
Selected Publications
- Putzke, J.; Fischbach, K.; Schoder, D.; and Gloor, P. A. (2010) The Evolution of Interaction Networks in Massively Multiplayer Online Games, Journal of the Association for Information Systems: Vol. 11: Iss. 2, Article 2. Available at: aisel.aisnet.org/jais/vol11/iss2/2
- Fischbach, K.; Schoder, D.; Gloor, P. (2009): Analysis of Informal Communication Networks – A Case Study. In: Business & Information Systems Engineering 1(2).
- Nann, S,; Krauss, J.S.; Schober, M.; Gloor, P.A.; Fischbach, K.; Fuehres, H. (2010): The Power of Alumni Networks - Success of Startup Companies Correlates with Online Social Network Structure of its Founders. CCI Working Paper 2010-001.
Available at: papers.ssrn.com/sol3/papers.cfm - Gloor, P.; Krauss, J.; Nann, S.; Fischbach, K.; Schoder, D. (2009): Identifying Trends through Semantic Social Network Analysis. In: Proceedings of the IEEE 2009 International Conference on Social Computing (SocialCom-09), August 29-31, Vancouver, Canada (Paper Acceptance Rate 9%)
- Wölfl, T.; Fischbach, K. (2007): A Method for the Certification and the Delegation of Trust in Distributed Systems, The First International Workshop on Trust and Reputation Management in Massively Distributed Computing Systems (TRAM 2007), in conjunction with IEEE ICDCS 2007, June 25-29, Toronto, Canada
- Schoder, D.; Fischbach, K.; Schmitt, C. (2005): P2P Application Areas, in: Steinmetz, R.; Wehrle, K. (eds.): Peer-to-Peer Systems and Applications (Lecture Notes in Computer Science Vol. 3485), Springer.
- Schoder, D.; Fischbach, K. (2003): Peer-to-Peer Prospects. In: Communications of the ACM, Feb. 2003, Vol. 46, Nr. 2, S. 27-29.