Detecting Trends in Social Bookmarking Systems: A del.icio.us Endeavor
Robert Wetzker,
Carsten Zimmermann and
Christian Bauckhage
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Robert Wetzker: Technische Universität Berlin, Germany
Carsten Zimmermann: University of San Diego, USA
Christian Bauckhage: University of Bonn and Fraunhofer IAIS, Germany
International Journal of Data Warehousing and Mining (IJDWM), 2010, vol. 6, issue 1, 38-57
Abstract:
The authors present and evaluate an approach to trend detection in social bookmarking systems using a probabilistic generative model in combination with smoothing techniques. Social bookmarking systems are gaining major interest among researchers in the areas of data mining and Web intelligence, since they provide a large amount of user-generated annotations and reflect the interest of millions of people. Based on a vast corpus of approximately 150 million bookmarks found at del. icio.us, the authors analyze bookmarking and tagging patterns and discuss evidence that social bookmarking systems are vulnerable to spamming. They present a method to limit the impact of spam on a trend detector and provide conclusions as well as directions for future research.
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jdwm00:v:6:y:2010:i:1:p:38-57
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