Tagging systems allow users to interactively annotate a pool of shared resources using descriptive tags. As tagging systems are gaining in popularity, they become more susceptible to <i>tag spam:</i> misleading tags that are generated in order to increase the visibility of some resources or simply to confuse users. We introduce a framework for modeling tagging systems and user tagging behavior. We also describe a method for ranking documents matching a tag based on taggers' reliability. Using our framework, we study the behavior of existing approaches under malicious attacks and the impact of a moderator and our ranking method.
%0 Conference Paper
%1 koutrika2007combating
%A Koutrika, Georgia
%A Effendi, Frans Adjie
%A Gyöngyi, Zoltán
%A Heymann, Paul
%A Garcia-Molina, Hector
%B Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
%C New York, NY, USA
%D 2007
%I ACM
%K folksonomy social-tagging spam-detection
%P 57--64
%R 10.1145/1244408.1244420
%T Combating spam in tagging systems
%U http://doi.acm.org/10.1145/1244408.1244420
%X Tagging systems allow users to interactively annotate a pool of shared resources using descriptive tags. As tagging systems are gaining in popularity, they become more susceptible to <i>tag spam:</i> misleading tags that are generated in order to increase the visibility of some resources or simply to confuse users. We introduce a framework for modeling tagging systems and user tagging behavior. We also describe a method for ranking documents matching a tag based on taggers' reliability. Using our framework, we study the behavior of existing approaches under malicious attacks and the impact of a moderator and our ranking method.
%@ 978-1-59593-732-2
@inproceedings{koutrika2007combating,
abstract = {Tagging systems allow users to interactively annotate a pool of shared resources using descriptive tags. As tagging systems are gaining in popularity, they become more susceptible to <i>tag spam:</i> misleading tags that are generated in order to increase the visibility of some resources or simply to confuse users. We introduce a framework for modeling tagging systems and user tagging behavior. We also describe a method for ranking documents matching a tag based on taggers' reliability. Using our framework, we study the behavior of existing approaches under malicious attacks and the impact of a moderator and our ranking method.},
acmid = {1244420},
added-at = {2012-07-01T20:30:39.000+0200},
address = {New York, NY, USA},
author = {Koutrika, Georgia and Effendi, Frans Adjie and Gy\"{o}ngyi, Zolt\'{a}n and Heymann, Paul and Garcia-Molina, Hector},
biburl = {https://www.bibsonomy.org/bibtex/21b91f36cb1fe00fdb5029882e227b79c/beate},
booktitle = {Proceedings of the 3rd international workshop on Adversarial information retrieval on the web},
description = {Combating spam in tagging systems},
doi = {10.1145/1244408.1244420},
interhash = {8b6de1f035a46f5465f1ed868a18c79a},
intrahash = {1b91f36cb1fe00fdb5029882e227b79c},
isbn = {978-1-59593-732-2},
keywords = {folksonomy social-tagging spam-detection},
location = {Banff, Alberta, Canada},
numpages = {8},
pages = {57--64},
publisher = {ACM},
series = {AIRWeb '07},
timestamp = {2012-07-01T20:30:39.000+0200},
title = {Combating spam in tagging systems},
url = {http://doi.acm.org/10.1145/1244408.1244420},
year = 2007
}