H. Halpin, V. Robu, und H. Shepherd. Proceedings of the 16th nternational World Wide Web Conference (WWW'07), New York, NY, USA, ACM Press, (2007)
Zusammenfassung
The debate within the Web community over the optimal means
by which to organize information often pits formalized classications
against distributed collaborative tagging systems. A number
of questions remain unanswered, however, regarding the nature of
collaborative tagging systems including whether coherent categorization
schemes can emerge from unsupervised tagging by users.
This paper uses data from the social bookmarking site del.icio.us to
examine the dynamics of collaborative tagging systems. In particular,
we examine whether the distribution of the frequency of use
of tags for popular sites with a long history (many tags and many
users) can be described by a power law distribution, often characteristic
of what are considered complex systems. We produce a
generative model of collaborative tagging in order to understand
the basic dynamics behind tagging, including how a power law distribution
of tags could arise. We empirically examine the tagging
history of sites in order to determine how this distribution arises
over time and to determine the patterns prior to a stable distribution.
Lastly, by focusing on the high-frequency tags of a site where
the distribution of tags is a stabilized power law, we show how tag
co-occurrence networks for a sample domain of tags can be used
to analyze the meaning of particular tags given their relationship to
other tags.
%0 Conference Paper
%1 Halpin_et_al_2007
%A Halpin, Harry
%A Robu, Valentin
%A Shepherd, Hana
%B Proceedings of the 16th nternational World Wide Web Conference (WWW'07)
%C New York, NY, USA
%D 2007
%I ACM Press
%K attachment co-occurence complex complexity distribution frequency model network preferential tagging tagora zipf
%T The Complex Dynamics of Collaborative Tagging
%U http://www2007.org/papers/paper635.pdf
%X The debate within the Web community over the optimal means
by which to organize information often pits formalized classications
against distributed collaborative tagging systems. A number
of questions remain unanswered, however, regarding the nature of
collaborative tagging systems including whether coherent categorization
schemes can emerge from unsupervised tagging by users.
This paper uses data from the social bookmarking site del.icio.us to
examine the dynamics of collaborative tagging systems. In particular,
we examine whether the distribution of the frequency of use
of tags for popular sites with a long history (many tags and many
users) can be described by a power law distribution, often characteristic
of what are considered complex systems. We produce a
generative model of collaborative tagging in order to understand
the basic dynamics behind tagging, including how a power law distribution
of tags could arise. We empirically examine the tagging
history of sites in order to determine how this distribution arises
over time and to determine the patterns prior to a stable distribution.
Lastly, by focusing on the high-frequency tags of a site where
the distribution of tags is a stabilized power law, we show how tag
co-occurrence networks for a sample domain of tags can be used
to analyze the meaning of particular tags given their relationship to
other tags.
@inproceedings{Halpin_et_al_2007,
abstract = {The debate within the Web community over the optimal means
by which to organize information often pits formalized classications
against distributed collaborative tagging systems. A number
of questions remain unanswered, however, regarding the nature of
collaborative tagging systems including whether coherent categorization
schemes can emerge from unsupervised tagging by users.
This paper uses data from the social bookmarking site del.icio.us to
examine the dynamics of collaborative tagging systems. In particular,
we examine whether the distribution of the frequency of use
of tags for popular sites with a long history (many tags and many
users) can be described by a power law distribution, often characteristic
of what are considered complex systems. We produce a
generative model of collaborative tagging in order to understand
the basic dynamics behind tagging, including how a power law distribution
of tags could arise. We empirically examine the tagging
history of sites in order to determine how this distribution arises
over time and to determine the patterns prior to a stable distribution.
Lastly, by focusing on the high-frequency tags of a site where
the distribution of tags is a stabilized power law, we show how tag
co-occurrence networks for a sample domain of tags can be used
to analyze the meaning of particular tags given their relationship to
other tags.},
added-at = {2007-05-25T23:45:57.000+0200},
address = {New York, NY, USA},
author = {Halpin, Harry and Robu, Valentin and Shepherd, Hana},
biburl = {https://www.bibsonomy.org/bibtex/2631924a8b2f1ab8a8e2c38a43f1dbc5f/andreab},
booktitle = {Proceedings of the 16th nternational World Wide Web Conference (WWW'07)},
date = {2007 May 8--12},
interhash = {0a44c162c87ebd3186879a070d2c8c9d},
intrahash = {631924a8b2f1ab8a8e2c38a43f1dbc5f},
keywords = {attachment co-occurence complex complexity distribution frequency model network preferential tagging tagora zipf},
location = {Banff, Canada},
publisher = {ACM Press},
timestamp = {2007-05-25T23:45:57.000+0200},
title = {The Complex Dynamics of Collaborative Tagging},
url = {http://www2007.org/papers/paper635.pdf},
year = 2007
}