Social bookmarking systems have recently gained interest among 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.
%0 Conference Paper
%1 wetzker08a
%A Wetzker, Robert
%A Zimmermann, Carsten
%A Bauckhage, Christian
%B Proceedings of the ECAI 2008 Mining Social Data Workshop
%D 2008
%I IOS Press
%K bookmarking delicious
%P 26--30
%T Analyzing Social Bookmarking Systems: A del.icio.us Cookbook
%U http://robertwetzker.com/wp-content/uploads/2008/06/wetzker_delicious_ecai2008_final.pdf
%X Social bookmarking systems have recently gained interest among 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.
@inproceedings{wetzker08a,
abstract = {Social bookmarking systems have recently gained interest among 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.},
added-at = {2009-04-11T17:10:14.000+0200},
author = {Wetzker, Robert and Zimmermann, Carsten and Bauckhage, Christian},
biburl = {https://www.bibsonomy.org/bibtex/24a118c143aa0d3b0de636ae7529e18ce/antares},
booktitle = {Proceedings of the ECAI 2008 Mining Social Data Workshop},
interhash = {cdd8d32ba6507335a3b856419afc71c3},
intrahash = {4a118c143aa0d3b0de636ae7529e18ce},
keywords = {bookmarking delicious},
owner = {korth},
pages = {26--30},
publisher = {IOS Press},
timestamp = {2009-04-11T17:10:14.000+0200},
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
}