Accurately Detecting Trolls In Slashdot Zoo Via Decluttering
ASONAM '14: Advances in Social Networks Analysis and Mining 2014 Beijing China August, 2014(2014)
摘要
Online social networks like Slashdot bring valuable information to millions of users - but their accuracy is based on the integrity of their user base. Unfortunately, there are many "trolls" on Slashdot who post misinformation and compromise system integrity. In this paper, we develop a general algorithm called TIA (short for Troll Identification Algorithm) to classify users of an online "signed" social network as malicious (e.g. trolls on Slashdot) or benign (i.e. normal honest users). Though applicable to many signed social networks, TIA has been tested on troll detection on Slashdot Zoo under a wide variety of parameter settings. Its running time is faster than many past algorithms and it is significantly more accurate than existing methods.
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关键词
social networking (online),Slashdot Zoo,TIA,decluttering,online signed social network,troll detection,troll identification algorithm
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