The Complexity of Finding Effectors

Laurent Bulteau, Stefan Fafianie, Vincent Froese, Rolf Niedermeier, Nimrod Talmon

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The NP-hard Effectors problem on directed graphs is motivated by applications in network mining, particularly concerning the analysis of probabilistic information-propagation processes in social networks. In the corresponding model the arcs carry probabilities and there is a probabilistic diffusion process activating nodes by neighboring activated nodes with probabilities as specified by the arcs. The point is to explain a given network activation state as well as possible by using a minimum number of “effector nodes”; these are selected before the activation process starts. We correct, complement, and extend previous work from the data mining community by a more thorough computational complexity analysis of Effectors, identifying both tractable and intractable cases. To this end, we also exploit a parameterization measuring the “degree of randomness” (the number of ‘really’ probabilistic arcs) which might prove useful for analyzing other probabilistic network diffusion problems as well.

Original languageEnglish
Pages (from-to)253-279
Number of pages27
JournalTheory of Computing Systems
Issue number2
StatePublished - 1 Feb 2017
Externally publishedYes


  • Exact algorithms
  • Influence maximization
  • Network activation
  • Parameterized complexity
  • Probabilistic information propagation
  • Social networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics


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