@misc{zlati2009hypergraph,
  abstract = {  Recent years have witnessed the emergence of a new class of social networks, that require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper[1] we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks. },
  author = {Zlatic, Vinko and Ghoshal, Gourab and Caldarelli, Guido},
  interhash = {7dfecf6636651d0b42d569a2ebb5212c},
  intrahash = {6b9803ae1a6f0c369d0420c7cf7b3559},
  note = {cite arxiv:0905.0976Comment: 8 pages, 9 figures, revtex},
  title = {Hypergraph topological quantities for tagged social networks},
  url = {http://arxiv.org/abs/0905.0976},
  year = 2009
}

@inproceedings{alkhalifa2007towards,
  acmid = {1286288},
  address = {New York, NY, USA},
  author = {Al-Khalifa, Hend S. and Davis, Hugh C.},
  booktitle = {Proceedings of the eighteenth conference on Hypertext and hypermedia},
  doi = {http://doi.acm.org/10.1145/1286240.1286288},
  interhash = {5af7b26ff2fcace33426fb74902e9cc0},
  intrahash = {d3fc5e2b6c2a58f46625288d40aa0de5},
  isbn = {978-1-59593-820-6},
  location = {Manchester, UK},
  numpages = {4},
  pages = {163--166},
  publisher = {ACM},
  series = {HT '07},
  title = {Towards better understanding of folksonomic patterns},
  url = {http://doi.acm.org/10.1145/1286240.1286288},
  year = 2007
}

@inproceedings{naaman2010really,
  abstract = {In this work we examine the characteristics of social activity and patterns of communication on Twitter, a prominent example of the emerging class of communication systems we call "social awareness streams." We use system data and message content from over 350 Twitter users, applying human coding and quantitative analysis to provide a deeper understanding of the activity of individuals on the Twitter network. In particular, we develop a content-based categorization of the type of messages posted by Twitter users, based on which we examine users' activity. Our analysis shows two common types of user behavior in terms of the content of the posted messages, and exposes differences between users in respect to these activities.},
  acmid = {1718953},
  address = {New York, NY, USA},
  author = {Naaman, Mor and Boase, Jeffrey and Lai, Chih-Hui},
  booktitle = {Proceedings of the 2010 ACM conference on Computer supported cooperative work},
  doi = {10.1145/1718918.1718953},
  interhash = {c6bf200b6532c60e125ba45d17c8d4cf},
  intrahash = {1066e1c098a8d7b67e7903069c6a7a9f},
  isbn = {978-1-60558-795-0},
  location = {Savannah, Georgia, USA},
  numpages = {4},
  pages = {189--192},
  publisher = {ACM},
  series = {CSCW '10},
  title = {Is it really about me?: message content in social awareness streams},
  url = {http://doi.acm.org/10.1145/1718918.1718953},
  year = 2010
}

@inproceedings{schmitz2006mining,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.},
  address = {Heidelberg},
  author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.},
  editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and �iberna, A.},
  file = {schmitz2006mining.pdf:schmitz2006mining.pdf:PDF},
  groups = {public},
  interhash = {9f407e0b779aba5b3afca7fb906f579b},
  intrahash = {ed504c16bc4eb561a9446bd98b10dca1},
  lastdatemodified = {2006-12-07},
  lastname = {Schmitz},
  month = {July},
  own = {notown},
  pages = {261--270},
  pdf = {schmitz06-mining.pdf},
  publisher = {Springer},
  read = {notread},
  series = {Studies in Classification, Data Analysis, and Knowledge Organization},
  timestamp = {2007-09-11 13:31:35},
  title = {Mining Association Rules in Folksonomies},
  username = {dbenz},
  year = 2006
}

@article{santosneto2009individual,
  author = {Santos-Neto, E. and Condon, D. and Andrade, N. and Iamnitchi, A. and Ripeanu, M.},
  booktitle = {Proceedings of the 20th ACM conference on Hypertext and hypermedia},
  interhash = {07a2f583edf181046a997bc59e7e56be},
  intrahash = {75da6d18a60db6c69d4f3cd2328abd58},
  organization = {ACM},
  pages = {183--192},
  title = {{Individual and social behavior in tagging systems}},
  url = {http://scholar.google.de/scholar.bib?q=info:78ozoF5AkegJ:scholar.google.com/&output=citation&hl=de&as_sdt=2000&ct=citation&cd=0},
  year = 2009
}

@article{strohmaier2008acquiring,
  address = {Los Alamitos, CA, USA},
  author = {Strohmaier, Markus and Prettenhofer, Peter and Kröll, Mark},
  doi = {http://doi.ieeecomputersociety.org/10.1109/WIIAT.2008.364},
  interhash = {c3708f588c62e94de5c056e708a24699},
  intrahash = {120d307a0a7391dc6a273a6e28743360},
  isbn = {978-0-7695-3496-1},
  journal = {Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on},
  pages = {602-605},
  publisher = {IEEE Computer Society},
  title = {Acquiring Explicit User Goals from Search Query Logs},
  url = {http://doi.ieeecomputersociety.org/10.1109/WIIAT.2008.364},
  volume = 3,
  year = 2008
}

@inproceedings{francisco2008clique,
  author = {Francisco, Alexandre P. and Baeza-Yates, Ricardo A. and Oliveira, Arlindo L.},
  booktitle = {SPIRE},
  crossref = {conf/spire/2008},
  date = {2008-11-24},
  editor = {Amir, Amihood and Turpin, Andrew and Moffat, Alistair},
  ee = {http://dx.doi.org/10.1007/978-3-540-89097-3_19},
  interhash = {3df2855b8d7c408298efcda601eac68c},
  intrahash = {42101c15dfe2345542627b51e623b165},
  isbn = {978-3-540-89096-6},
  pages = {188-199},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Clique Analysis of Query Log Graphs.},
  url = {http://dblp.uni-trier.de/db/conf/spire/spire2008.html#FranciscoBO08},
  volume = 5280,
  year = 2008
}

@inproceedings{cattuto2007vocabulary,
  abstract = { We analyze a large-scale snapshot of del.icio.us and investigate how the number of different tags in the system grows as a function of a suitably defined notion of time. We study the temporal evolution of the global vocabulary size, i.e. the number of distinct tags in the entire system, as well as the evolution of local vocabularies, that is the growth of the number of distinct tags used in the context of a given resource or user. In both cases, we find power-law behaviors with exponents smaller than one. Surprisingly, the observed growth behaviors are remarkably regular throughout the entire history of the system and across very different resources being bookmarked. Similar sub-linear laws of growth have been observed in written text, and this qualitative universality calls for an explanation and points in the direction of non-trivial cognitive processes in the complex interaction patterns characterizing collaborative tagging.},
  author = {Cattuto, Ciro and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio},
  interhash = {7de017393b2d48335e209a9db23e08b6},
  intrahash = {fb163dd424fa1eb40640340f27ee0ea4},
  title = {Vocabulary growth in collaborative tagging systems},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0704.3316},
  year = 2007
}

@inproceedings{schmitz2006mining,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.},
  address = {Heidelberg},
  author = {Schmitz, Christoph and Hotho, Andreas and J�schke, Robert and Stumme, Gerd},
  booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.},
  editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and �iberna, A.},
  file = {schmitz2006mining.pdf:schmitz2006mining.pdf:PDF},
  interhash = {9f407e0b779aba5b3afca7fb906f579b},
  intrahash = {91a9a847b72a77e8f7d7db4de52716e5},
  lastdatemodified = {2006-12-07},
  lastname = {Schmitz},
  month = {July},
  own = {notown},
  pages = {261--270},
  pdf = {schmitz06-mining.pdf},
  publisher = {Springer},
  read = {notread},
  series = {Studies in Classification, Data Analysis, and Knowledge Organization},
  title = {Mining Association Rules in Folksonomies},
  year = 2006
}

@inproceedings{baezayates2007extracting,
  abstract = {In this paper we study a large query log of more than twenty million queries with the goal of extracting the semantic relations that are implicitly captured in the actions of users submitting queries and clicking answers. Previous query log analyses were mostly done with just the queries and not the actions that followed after them. We first propose a novel way to represent queries in a vector space based on a graph derived from the query-click bipartite graph. We then analyze the graph produced by our query log, showing that it is less sparse than previous results suggested, and that almost all the measures of these graphs follow power laws, shedding some light on the searching user behavior as well as on the distribution of topics that people want in the Web. The representation we introduce allows to infer interesting semantic relationships between queries. Second, we provide an experimental analysis on the quality of these relations, showing that most of them are relevant. Finally we sketch an application that detects multitopical URLs.},
  address = {New York, NY, USA},
  author = {Baeza-Yates, Ricardo and Tiberi, Alessandro},
  booktitle = {KDD '07: Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining},
  doi = {http://doi.acm.org/10.1145/1281192.1281204},
  file = {baezayates2007extracting.pdf:baezayates2007extracting.pdf:PDF},
  groups = {public},
  interhash = {26ca034be705abaf072835784f53d877},
  intrahash = {6e45b65feffd1545c6dca62bf4b8f53d},
  isbn = {978-1-59593-609-7},
  location = {San Jose, California, USA},
  pages = {76--85},
  publisher = {ACM},
  timestamp = {2009-06-01 15:31:03},
  title = {Extracting semantic relations from query logs},
  url = {http://portal.acm.org/citation.cfm?id=1281192.1281204},
  username = {dbenz},
  year = 2007
}