Encyclopedia of Social Network Analysis and Mining

Living Edition
| Editors: Reda Alhajj, Jon Rokne

Actor-Based Models for Longitudinal Networks

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7163-9_166-1

Synonyms

Glossary

Actors

Nodes of the network graph

Behavior

Changing characteristics of actors

Covariates

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

Dyad

Pair of actors of the network

Dyadic Indicator

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

Effects

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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Notes

Acknowledgments

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

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© 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