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A guide to choosing and implementing reference models for social network analysis.

Elizabeth A Hobson1, Matthew J Silk2, Nina H Fefferman3

  • 1Department of Biological Sciences, University of Cincinnati, 318 College Drive, Cincinnati, OH, 45221, U.S.A.

Biological Reviews of the Cambridge Philosophical Society
|July 3, 2021
PubMed
Summary
This summary is machine-generated.

Analyzing social networks requires specialized statistical methods. This review details randomization procedures for creating reference models, crucial for hypothesis testing in social network analysis.

Keywords:
agent-based modelanimal socialityconfiguration modelpermutationrandomizationsocial network analysis

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Area of Science:

  • Social Network Analysis
  • Statistics
  • Computational Social Science

Background:

  • Analyzing relational data in social networks presents unique statistical challenges.
  • Standard methods are often insufficient due to the complex dependencies within network structures.

Purpose of the Study:

  • To review various randomization procedures for generating reference models in social network analysis.
  • To enhance researchers' understanding and confidence in applying these analytical approaches.

Main Methods:

  • Discussion of key stages in developing effective reference models.
  • Detailed explanation of four approaches: permutation, resampling, sampling from a distribution, and generative models.
  • Illustration with examples from a simulated social system.

Main Results:

  • Reference models are essential for hypothesis testing in network analysis by providing expected outcomes.
  • Different randomization approaches are suitable for various research questions and data types.
  • Potential pitfalls in generating reference models are identified.

Conclusions:

  • A deeper understanding of reference model generation improves the rigor of social network analysis.
  • Researchers can confidently tailor reference models to specific hypotheses and network data.
  • The reviewed methods offer a robust framework for analyzing complex social systems.