How even tiny influence can have a big impact!

Barbara Keller, David Peleg, Roger Wattenhofer

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

6 Scopus citations


An influence network is a graph where each node changes its state according to a function of the states of its neighbors. We present bounds for the stabilization time of such networks. We derive a general bound for the classic "Democrats and Republicans" problem and study different model modifications and their influence on the way of stabilizing and their stabilization time. Our main contribution is an exponential lower and upper bound on weighted influence networks. We also investigate influence networks with asymmetric weights and show an influence network with an exponential cycle length in the stable situation.

Original languageEnglish
Title of host publicationFun with Algorithms - 7th International Conference, FUN 2014, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319078892
StatePublished - 2014
Externally publishedYes
Event7th International Conference on Fun with Algorithms, FUN 2014 - Sicily, Italy
Duration: 1 Jul 20143 Jul 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8496 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Conference on Fun with Algorithms, FUN 2014


  • Asymmetric Graphs
  • Equilibrium
  • Influence Networks
  • Majority Function
  • Social Networks
  • Stabilization
  • Weighted Graphs


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