Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
ACM Transactions on Internet Technology (TOIT)
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Probability and Computing: Randomized Algorithms and Probabilistic Analysis
Sybilproof reputation mechanisms
Proceedings of the 2005 ACM SIGCOMM workshop on Economics of peer-to-peer systems
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Detecting colluders in pagerank: finding slow mixing states in a markov chain
Detecting colluders in pagerank: finding slow mixing states in a markov chain
Link spam detection based on mass estimation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient
SIAM Journal on Numerical Analysis
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
On the α-Sensitivity of Nash Equilibria in PageRank-Based Network Reputation Games
FAW '09 Proceedings of the 3d International Workshop on Frontiers in Algorithmics
Hybrid transitive trust mechanisms
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Foundations and Trends in Information Retrieval
Benefits of bias: towards better characterization of network sampling
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
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Popular reputation systems for linked networks can be manipulated by spammers who strategically place links. The reputation of node v is interpreted as the world's opinion of v's importance. In PageRank [4], v's own opinion can be seen to have considerable influence on her reputation, where v expresses a high opinion of herself by participating in short directed cycles. In contrast, we show that expected hitting time -- the time to reach v in a random walk -- measures essentially the same quantity as PageRank, but excludes v's opinion. We make these notions precise, and show that a reputation system based on hitting time resists tampering by individuals or groups who strategically place outlinks. We also present an algorithm to efficiently compute hitting time for all nodes in a massive graph; conventional algorithms do not scale adequately.