Modelling Dyadic Interaction with Hawkes Processes

Peter F. Halpin, Paul De Boeck

Research output: Contribution to journalArticlepeer-review


We apply the Hawkes process to the analysis of dyadic interaction. The Hawkes process is applicable to excitatory interactions, wherein the actions of each individual increase the probability of further actions in the near future. We consider the representation of the Hawkes process both as a conditional intensity function and as a cluster Poisson process. The former treats the probability of an action in continuous time via non-stationary distributions with arbitrarily long historical dependency, while the latter is conducive to maximum likelihood estimation using the EM algorithm. We first outline the interpretation of the Hawkes process in the dyadic context, and then illustrate its application with an example concerning email transactions in the work place.

Original languageEnglish (US)
Pages (from-to)793-814
Number of pages22
Issue number4
StatePublished - Oct 2013


  • EM algorithm
  • Hawkes processes
  • dyadic interaction
  • event sampling
  • maximum likelihood

ASJC Scopus subject areas

  • General Psychology
  • Applied Mathematics


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