Method for countering social bookmarking pollution using user similarities

Abstract

In this paper, we propose a method for countering social bookmark pollution. First, we investigate the characteristics of social bookmark pollution and show that high similarities in the user bookmarks result in social bookmark pollution. Then, we discuss a bookmark number reduction method based on user similarities between the user bookmarks. We evaluate the proposed method by applying it to Hatena Bookmark. It is found that the proposed method only slightly reduces the bookmark number of the Web pages that are not affected by social bookmark pollution but greatly reduces the bookmark number of those Web pages that are affected by social bookmark pollution. © 2010 Springer-Verlag.