Analyzing Social Bookmarking Systems: A del.icio.us Cookbook Export

@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.}, author = {Wetzker, Robert and Zimmermann, Carsten and Bauckhage, Christian}, booktitle = {Proceedings of the ECAI 2008 Mining Social Data Workshop}, citeulike-article-id = {3727433}, citeulike-linkout-0 = {http://robertwetzker.com/wp-content/uploads/2008/06/wetzker_delicious_ecai2008_final.pdf}, keywords = {2008-bookmarking-delicious-delicious-ecai-folksonomy}, pages = {26--30}, posted-at = {2008-11-29 15:20:44}, priority = {2}, publisher = {IOS Press}, 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} }

TY - CONF ID - wetzker08a L3 - citeulike-article-id:3727433 N2 - 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. EP - 30 TI - Analyzing Social Bookmarking Systems: A del.icio.us Cookbook PB - IOS Press T2 - Proceedings of the ECAI 2008 Mining Social Data Workshop SP - 26 KW - 2008-bookmarking-delicious-delicious-ecai-folksonomy AU - Wetzker, Robert AU - Zimmermann, Carsten AU - Bauckhage, Christian PY - 2008/// UR - http://robertwetzker.com/wp-content/uploads/2008/06/wetzker_delicious_ecai2008_final.pdf ER -