@misc{golder05structure,
  author = {Golder, Scott and Huberman, Bernardo A.},
  citeulike-article-id = {305755},
  eprint = {cs.DL/0508082},
  interhash = {2d312240f16eba52c5d73332bc868b95},
  intrahash = {f852d7a909fa3edceb04abb7d2a20f71},
  month = Aug,
  priority = {2},
  title = {The Structure of Collaborative Tagging Systems},
  url = {http://arxiv.org/abs/cs.DL/0508082},
  year = 2005
}

@inproceedings{koerner2010thinking,
  abstract = {Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence  of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.},
  address = {Raleigh, NC, USA},
  author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)},
  interhash = {5afe6e4ce8357d8ac9698060fb438468},
  intrahash = {45f8d8f2a8251a5e988c596a5ebb3f2d},
  month = apr,
  publisher = {ACM},
  title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity},
  url = {http://www.kde.cs.uni-kassel.de/benz/papers/2010/koerner2010thinking.pdf},
  year = 2010
}

@article{10.1109/TKDE.2012.115,
  address = {Los Alamitos, CA, USA},
  author = {Zubiaga, Arkaitz and Fresno, Victor and Martinez, Raquel and Garcia-Plaza, Alberto P.},
  doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.115},
  interhash = {f2e961e2b99fec0634b0d4fa3e001282},
  intrahash = {8a25332bfeb33e2ad8e1e1a062976da2},
  issn = {1041-4347},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  number = {PrePrints},
  publisher = {IEEE Computer Society},
  title = {Harnessing Folksonomies to Produce a Social Classification of Resources},
  volume = 99,
  year = 2012
}

@article{tonkin2006folksonomies,
  abstract = {A folksonomy is a type of distributed classification system. It is usually created by a group of individuals, typically the resource users. Users add tags to online items, such as images, videos, bookmarks and text. These tags are then shared and sometimes refined. In this article we look at what makes folksonomies work. We agree with the premise that tags are no replacement for formal systems, but we see this as being the core quality that makes folksonomy tagging so useful.},
  author = {Tonkin, Emma and Guy, Marieke},
  file = {tonkin2006folksonomies.pdf:tonkin2006folksonomies.pdf:PDF},
  interhash = {535e0aea1bcbd7feb85a7495f284a589},
  intrahash = {f56571b67b4e70a7d108dc8529d4c937},
  journal = {D-Lib},
  lastdatemodified = {2006-07-18},
  lastname = {Tonkin},
  location = {San Diego, California},
  month = {January},
  number = 1,
  own = {own},
  pdf = {tonkin06-folksonomies.pdf},
  read = {read},
  title = {Folksonomies: Tidying Up Tags?},
  url = {http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=2000478},
  volume = 12,
  year = 2006
}

@inproceedings{wetzker2008analyzing,
  abstract = {Social bookmarking systems have recently gained interestamong researches in the areas of data mining and web intelligence, as they provide a vast amount of user-generated annotations and reflect the interests of millions of people. In this paper, we discuss our initial findings obtained from analyzing a vast corpus of almost 150 million bookmarks found at del.icio.us. Apart from investigating bookmarking and tagging patterns in this data, we discuss evidence that social bookmarking systems are vulnerable to spamming and hence need to be preprocessed before any insightful analysis can be carried out. We present a method, which limits the influence of spam in social bookmarking analysis and provide conclusions and directions for future research.},
  author = {Wetzker, Robert and Zimmermann, Carsten and Bauckhage, Christian},
  booktitle = {Mining Social Data (MSoDa) Workshop Proceedings},
  interhash = {cdd8d32ba6507335a3b856419afc71c3},
  intrahash = {c71aa17db3959585ed3320dcefe7f39b},
  month = {July},
  organization = {ECAI 2008},
  pages = {26-30},
  title = {Analyzing Social Bookmarking Systems: A del.icio.us Cookbook},
  url = {http://robertwetzker.com/wp-content/uploads/2008/06/wetzker_delicious_ecai2008_final.pdf},
  year = 2008
}

@misc{mejiasdeli,
  author = {Mejias, Ulises Ali},
  day = 27,
  interhash = {d25115b4f09147f7c492acb0b92a6d74},
  intrahash = {a79c527926c7d8b07de5f14668b7890d},
  month = {December},
  title = {A del.icio.us study},
  url = {http://ideant.typepad.com/ideant/2004/12/a_delicious_stu.html},
  year = 2004
}