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Siena: Statistical Modeling of Longitudinal Network Data

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Recommended Reading

  • In addition to the help pages that are available as for all R packages, there is an extensive manual (Ripley et al. 2017) and a tutorial paper (Snijders et al. 2010b). A textbook about the Siena method and an edited volume with example applications are in preparation. The website http://www.stats.ox.ac.uk/siena/ is actively maintained and contains references to the basic methodology, references to applications, R scripts, example data sets, workshop announcements, and more

  • For those who wish to read more about the mathematical and methodological background, a recommended sequence of readings could be Snijders (1996) as an introduction to the idea of stochastic actor-oriented models, Snijders (2001) or Snijders (2005) for the basic definition of the model for one dependent network defined as a changing digraph, and Steglich et al. (2010) for models for the dynamics of networks and behavior, which might be followed by Snijders et al. (2010a) for Maximum Likelihood estimation or Snijders et al. (2013) for models with multiple dependent networks.

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Acknowledgements

Work on the Siena method and software has taken place at the University of Groningen (Department of Sociology) and the University of Oxford (Department of Statistics; Department of Politics and International Relations; Nuffield College). NWO (the Netherlands Organisation for Scientific Research) has supported development of this methodology and software through the project Statistical Methods for the Joint Development of Individual Behavior and Peer Networks (project number 575-28-012, researcher Mark Huisman), the integrated research program The Dynamics of Networks and Behavior (project number 401-01-550, methodological researchers Christian Steglich and Michael Schweinberger), and the ECRP-Eurocores program Models for the Evolution of Networks and Behavior (project number 461-05-690, methodological researcher Christian Steglich). The US National Institutes of Health have provided funding for methodological developments (Johan Koskinen) and software development (Ruth Ripley and Krists Boitmanis) as part of the project Adolescent Peer Social Network Dynamics and Problem Behavior (grant number 1R01HD052887-01A2).

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Authors and Affiliations

  1. Department of Sociology, University of Groningen, Groningen, The Netherlands

    Tom A. B. Snijders

  2. Department of Statistics and Nuffield College, University of Oxford, Oxford, UK

    Tom A. B. Snijders

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  1. Tom A. B. Snijders
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Correspondence to Tom A. B. Snijders .

Editor information

Editors and Affiliations

  1. Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. University of Calgary Computer Science, Calgary, Canada

    Jon Rokne

Section Editor information

  1. Department of Mathematics, University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

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Snijders, T.A.B. (2017). Siena: Statistical Modeling of Longitudinal Network Data. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_312-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_312-1

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  • Print ISBN: 978-1-4614-7163-9

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