• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Manipulation-resistant reputations using hitting time (2007)

Cached

  • Download as a PDF

Download Links

  • [www.cs.cornell.edu]
  • [web.engr.oregonstate.edu]
  • [people.cs.umass.edu]
  • [www.cs.cornell.edu]
  • [web.engr.oregonstate.edu]
  • [people.cs.umass.edu]
  • [research.microsoft.com]
  • [research.microsoft.com]
  • [research.microsoft.com]
  • [www.cs.cornell.edu]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by John Hopcroft , Daniel Sheldon
Citations:22 - 2 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Hopcroft07manipulation-resistantreputations,
    author = {John Hopcroft and Daniel Sheldon},
    title = {Manipulation-resistant reputations using hitting time},
    year = {2007}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

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.

Keyphrases

hitting time    manipulation-resistant reputation    world opinion    random walk    popular reputation system    high opinion    reputation system    considerable influence    massive graph    time resists    conventional algorithm   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University