Encyclopedia of Social Network Analysis and Mining

Living Edition
| Editors: Reda Alhajj, Jon Rokne

Actor-Based Models for Longitudinal Networks

  • Alberto Caimo
  • Nial Friel
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7163-9_166-1




Nodes of the network graph


Changing characteristics of actors


Variables which can depend on the actors (actor covariates) or on pairs of actors (dyadic covariates). They are considered “exogenous” variables in the sense that they are not determined by the stochastic process underlying the model


Pair of actors of the network

Dyadic Indicator

Binary variable indicating the presence or absence of a tie between two actors


Specifications of the objective function

Longitudinal Networks

Repeated measures of networks over time

Markov Chain

Stochastic process where the probability of future states given the present state does not depend on past states

Method of Moments

Statistical estimation method consisting of equating sample moments of a distribution with unobserved theoretic moments in order to get an approximation to the solutions of the likelihood equations

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Nial Friel’s research was supported by a Science Foundation Ireland Research Frontiers Program grant, 09/RFP/MTH2199.


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Copyright information

© Springer Science+Business Media LLC 2016

Authors and Affiliations

  1. 1.Faculty of Economics, University of LuganoLuganoSwitzerland
  2. 2.INSIGHT: The National Centre for Big Data Analytics, School of Mathematical Sciences, University College DublinDublinIreland

Section editors and affiliations

  • Suheil Khoury
    • 1
  1. 1.American University of SharjahSharjahUnited Arab Emirates