@article{cattuto2007network,
  author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd},
  editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen},
  interhash = {fc5f2df61d28bc99b7e15029da125588},
  intrahash = {da6c676c5664017247c7564fc247b190},
  issn = {0921-7126},
  journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''},
  number = 4,
  pages = {245-262},
  publisher = {IOS Press},
  title = {Network Properties of Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf},
  vgwort = {67},
  volume = 20,
  year = 2007
}

@inproceedings{cattuto2008semantic,
  abstract = {Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For tasks
like synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.},
  address = {Heidelberg},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008},
  editor = {Sheth, Amit P. and Staab, Steffen and Dean, Mike and Paolucci, Massimo and Maynard, Diana and Finin, Timothy W. and Thirunarayan, Krishnaprasad},
  interhash = {b44538648cfd476d6c94e30bc6626c86},
  intrahash = {27198c985b3bdb6daab0f7e961b370a9},
  pages = {615--631},
  publisher = {Springer},
  series = {LNAI},
  title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems},
  url = {http://dx.doi.org/10.1007/978-3-540-88564-1_39},
  volume = 5318,
  year = 2008
}

@inproceedings{1526808,
  abstract = {In this paper we give models and algorithms to describe and analyze the collaboration among authors of Wikipedia from a network analytical perspective. The edit network encodes who interacts how with whom when editing an article; it significantly extends previous network models that code author communities in Wikipedia. Several characteristics summarizing some aspects of the organization process and allowing the analyst to identify certain types of authors can be obtained from the edit network. Moreover, we propose several indicators characterizing the global network structure and methods to visualize edit networks. It is shown that the structural network indicators are correlated with quality labels of the associated Wikipedia articles.},
  address = {New York, NY, USA},
  author = {Brandes, Ulrik and Kenis, Patrick and Lerner, J\"{u}rgen and van Raaij, Denise},
  booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web},
  doi = {http://doi.acm.org/10.1145/1526709.1526808},
  interhash = {1d0c41c49ae3821dbde05fe6e34d0a4a},
  intrahash = {3569586bacbec77f6da6db5461db7857},
  isbn = {978-1-60558-487-4},
  location = {Madrid, Spain},
  pages = {731--740},
  publisher = {ACM},
  title = {Network analysis of collaboration structure in Wikipedia},
  url = {http://portal.acm.org/citation.cfm?id=1526808},
  year = 2009
}

@inproceedings{1367620,
  abstract = {We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and patterns that emerge from the collective dynamics of large numbers of people, rather than the actions and characteristics of individuals. The dataset contains summary properties of 30 billion conversations among 240 million people. From the data, we construct a communication graph with 180 million nodes and 1.3 billion undirected edges, creating the largest social network constructed and analyzed to date. We report on multiple aspects of the dataset and synthesized graph. We find that the graph is well-connected and robust to node removal. We investigate on a planetary-scale the oft-cited report that people are separated by "six degrees of separation" and find that the average path length among Messenger users is 6.6. We find that people tend to communicate more with each other when they have similar age, language, and location, and that cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.},
  address = {New York, NY, USA},
  author = {Leskovec, Jure and Horvitz, Eric},
  booktitle = {WWW '08: Proceeding of the 17th international conference on World Wide Web},
  doi = {http://doi.acm.org/10.1145/1367497.1367620},
  interhash = {27d7144813bb85492b18cad6cf6525e7},
  intrahash = {bfe758ce74fac01c2108c3f2184d6c48},
  isbn = {978-1-60558-085-2},
  location = {Beijing, China},
  pages = {915--924},
  publisher = {ACM},
  title = {Planetary-scale views on a large instant-messaging network},
  url = {http://portal.acm.org/citation.cfm?id=1367620},
  year = 2008
}