BibSonomy :: bibtex  ::

tag user group author concept BibTeX key search:all search:chriskoerner
A blue social bookmark and publication sharing system.
tags · relations · groups · popular
help · blog · about
login · register
chriskoerner's BibTeX entry:  

The Structure of Collaborative Tagging Systems

Journal of Information Science, 32(2): 198-208, 2006.
Authors: Scott A. Golder and Bernardo A. Huberman
URL: http://www.hpl.hp.com/research/idl/papers/tags/tags.pdf
Tags: social_networks tagging
Abstract: Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.
| URL | BibTeX  
@article{Golder2006,
title = {The Structure of Collaborative Tagging Systems},
author = {Scott A. Golder and Bernardo A. Huberman},
journal = {Journal of Information Science},
number = {2},
pages = {198-208},
url = {http://www.hpl.hp.com/research/idl/papers/tags/tags.pdf},
volume = {32},
year = {2006},
abstract = {Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.},
keywords = {social_networks tagging }
}