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Social networks spread rumors in sublogarithmic time

  • Max-Planck-Institut fur Informatik
  • Universität des Saarlandes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the prevalence of social networks, it has become increasingly important to understand their features and limitations. It has been observed that information spreads extremely fast in social networks. We study the performance of randomized rumor spreading protocols on graphs in the preferential attachment model. The well-known random phone call model of Karp et al. (FOCS 2000) is a push-pull strategy where in each round, each vertex chooses a random neighbor and exchanges information with it. We prove the following. • The push-pull strategy delivers a message to all nodes within Θ(log n) rounds with high probability. The best known bound so far was O(log2 n). • If we slightly modify the protocol so that contacts are chosen uniformly from all neighbors but the one contacted in the previous round, then this time reduces to Θ(log n / log log n), which is the diameter of the graph. This is the first time that a sublogarithmic broadcast time is proven for a natural setting. Also, this is the first time that avoiding double-contacts reduces the run-time to a smaller order of magnitude.

Original languageEnglish
Title of host publicationSTOC'11 - Proceedings of the 43rd ACM Symposium on Theory of Computing
PublisherAssociation for Computing Machinery
Pages21-30
Number of pages10
ISBN (Print)9781450306911
DOIs
Publication statusPublished - 1 Jan 2011
Externally publishedYes
Event43rd ACM Symposium on Theory of Computing, STOC 2011 - San Jose, United States
Duration: 6 Jun 20118 Jun 2011

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
ISSN (Print)0737-8017

Conference

Conference43rd ACM Symposium on Theory of Computing, STOC 2011
Country/TerritoryUnited States
CitySan Jose
Period6/06/118/06/11

Keywords

  • randomized algorithms
  • rumor spreading
  • social network

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