Controllability of network opinion in erdos–r ényi graphs using sparse control inputs

Geethu Joseph, Buddhika Nettasinghe, Vikram Krishnamurthy, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


This paper considers a social network modeled as an Erdos–Rényi random graph. Each individual in the network updates her opinion using the weighted average of the opinions of her neighbors. We explore how an external manipulative agent can drive the opinions of these individuals to a desired state with a limited additive influence on their innate opinions. We show that the manipulative agent can steer the network opinion to any arbitrary value in finite time (i.e., the system is controllable) almost surely when there is no restriction on her influence. However, when the control input is sparsity constrained, the network opinion is controllable with some probability. We lower bound this probability using the concentration properties of random vectors based on the Lévy concentration function and small ball probabilities. Our theoretical and numerical results shed light on how controllability of the network opinion depends on the parameters such as the size and the connectivity of the network and sity constraints faced by the manipulative agent.

Original languageEnglish (US)
Pages (from-to)2321-2345
Number of pages25
JournalSIAM Journal on Control and Optimization
Issue number3
StatePublished - 2021
Externally publishedYes


  • Concentration inequalities
  • Erdos–Rényi graph
  • Linear propagation
  • Social network opinion
  • Sparse controllability

ASJC Scopus subject areas

  • Control and Optimization
  • Applied Mathematics


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