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Deterministic blockmodelling of signed and two-mode networks: A tutorial with software and psychological examples.

Michael Brusco1, Patrick Doreian2,3, Douglas Steinley4

  • 1Florida State University, Tallahassee, Florida, USA.

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Summary

Deterministic blockmodelling, a social network analysis technique, offers valuable insights into group structures. This study introduces accessible methods and software for psychological researchers to apply this clustering approach effectively.

Keywords:
deterministic blockmodellingheuristicssocial network analysisstructural balance theorytwo-mode networks

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Area of Science:

  • Social network analysis
  • Psychological research methods

Background:

  • Deterministic blockmodelling is a clustering method for social network analysis.
  • Its application in psychological research is limited due to unfamiliarity, perceived lack of value, and software unavailability.

Purpose of the Study:

  • To provide a tutorial on deterministic blockmodelling for psychological research.
  • To introduce two key applications: structural balance and two-mode partitioning.
  • To present new software tools for implementing these methods in R.

Main Methods:

  • A tutorial framework for deterministic blockmodelling.
  • Description of structural balance and structural equivalence partitioning.
  • Development and demonstration of Fortran-based software for R.

Main Results:

  • The study offers a clear framework and practical examples of blockmodelling in psychology.
  • New software facilitates the implementation of advanced network analysis techniques.
  • Demonstrations show the utility of blockmodelling for analyzing psychological networks.

Conclusions:

  • Deterministic blockmodelling can be effectively applied in psychological research.
  • The provided tutorial and software address barriers to adoption.
  • This work encourages greater use of network analysis for understanding psychological phenomena.