@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
}

@article{cattuto2007network,
  abstract = {Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures - so-called folksonomies - as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them.  Subsequently, we introduce a network of tag co-occurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam. },
  address = {Amsterdam, The Netherlands},
  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},
  interhash = {fc5f2df61d28bc99b7e15029da125588},
  intrahash = {f15cc7613101babb2c3ed1927e35213a},
  issn = {0921-7126},
  journal = {AI Communications},
  month = dec,
  number = 4,
  pages = {245--262},
  publisher = {IOS Press},
  title = {Network Properties of Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2007network.pdf},
  volume = 20,
  year = 2007
}