DocumentCode :
3155315
Title :
Detecting Social Bookmark Spams Using Multiple User Accounts
Author :
Sakakura, Yoshiaki ; Amagasa, Toshiyuki ; Kitagawa, Hiroyuki
Author_Institution :
Grad. Sch. of SIE, Univ. of Tsukuba, Tsukuba, Japan
fYear :
2012
fDate :
26-29 Aug. 2012
Firstpage :
1153
Lastpage :
1158
Abstract :
This paper proposes a scheme of detecting "Intensive Bookmarking using Multiple Accounts" (IBMA), where many social bookmark accounts are used to create bookmark entries linking to the target web resources with the aim of increasing site visitors or optimizing search result ranking. To efficiently detect IBMA, we propose to use clustering social bookmark user accounts according to the similarity with respect to the book marked web resources or web sites. Specifically, we cluster users who create bookmarks linking to similar set of web resources or web sites. For this, we propose three similarity measurements over two sets of bookmarks. We experimentally show that the proposed scheme successfully detects IBMA spammers in a real dataset. We also evaluate the accuracy of the proposed scheme with varying the similarity measurements, and characterize them.
Keywords :
Internet; social networking (online); IBMA; Web resources; Web sites; bookmarked Web resources; intensive bookmarking using multiple accounts; multiple user accounts; social bookmark accounts; social bookmark spams; social bookmark user account clustering; Blogs; Educational institutions; Tagging; Unsolicited electronic mail; Web pages; data mining; social bookmark; spam detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
Type :
conf
DOI :
10.1109/ASONAM.2012.199
Filename :
6425601
Link To Document :
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