@article{benz2010social,
  abstract = {Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.},
  address = {Berlin/Heidelberg},
  author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd},
  doi = {10.1007/s00778-010-0208-4},
  interhash = {57fe43734b18909a24bf5bf6608d2a09},
  intrahash = {c9437d5ec56ba949f533aeec00f571e3},
  issn = {1066-8888},
  journal = {The VLDB Journal},
  month = dec,
  number = 6,
  pages = {849--875},
  publisher = {Springer},
  title = {The Social Bookmark and Publication Management System {BibSonomy}},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2010social.pdf},
  volume = 19,
  year = 2010
}

@inproceedings{mitzlaff2010visit,
  abstract = {The ongoing spread of online social networking and sharing sites has reshaped the way how people interact with each other. Analyzing the relatedness of different users within the resulting large populations of these systems plays an important role for tasks like user recommendation or community detection. Algorithms in these fields typically face the problem that explicit user relationships (like friend lists) are often very sparse. Surprisingly, implicit evidences (like click logs) of user relations have hardly been considered to this end. Based on our long-time experience with running BibSonomy [4], we identify in this paper different evidence networks of user relationships in our system. We broadly classify each network based on whether the links are explicitly established by the users (e.g., friendship or group membership) or accrue implicitly in the running system (e.g., when user u copies an entry of user v). We systematically analyze structural properties of these networks and whether topological closeness (in terms of the length of shortest paths) coincides with semantic similarity between users.},
  address = {New York, NY, USA},
  author = {Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas},
  booktitle = {HT '10: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia},
  doi = {10.1145/1810617.1810664},
  interhash = {5584c4c57fcd8eb4663df8b114bcf09c},
  intrahash = {6628bf43e3834ba147a22992f2f534e9},
  isbn = {978-1-4503-0041-4},
  location = {Toronto, Ontario, Canada},
  pages = {265--270},
  publisher = {ACM},
  title = {Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy},
  url = {http://portal.acm.org/citation.cfm?id=1810617.1810664},
  year = 2010
}