Capocci, A.; Rao, F. & Caldarelli, G.: Taxonomy and clustering in collaborative systems: the case of the on-line encyclopedia Wikipedia. , 2007
[Volltext]
In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia. We find a statistical similarity in the distributions of community sizes both by using the top-down approach of the categories division present in the archive and in the bottom-up procedure of community detection given by an algorithm based on the spectral properties of the graph. Regardless the statistically similar behaviour the two methods provide a rather different division of the articles, thereby signaling that the nature and presence of power laws is a general feature for these systems and cannot be used as a benchmark to evaluate the suitability of a clustering method.
@misc{capocci2007taxonomy,
author = {Capocci, A. and Rao, F. and Caldarelli, G.},
title = {Taxonomy and clustering in collaborative systems: the case of the on-line encyclopedia Wikipedia},
year = {2007},
url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0710.3058},
keywords = {clustering, taxonomy, comparison, toread, wikipedia},
abstract = { In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia. We find a statistical similarity in the distributions of community sizes both by using the top-down approach of the categories division present in the archive and in the bottom-up procedure of community detection given by an algorithm based on the spectral properties of the graph. Regardless the statistically similar behaviour the two methods provide a rather different division of the articles, thereby signaling that the nature and presence of power laws is a general feature for these systems and cannot be used as a benchmark to evaluate the suitability of a clustering method.}
}