Bayesian multiplex network models in R using STRAND: methods for biologists and social scientists.

Area of Science:

• Social network analysis
• Ecology
• Behavioral biology
• Economics

Background:

• Real-world social interactions are often multi-layered, forming complex multiplex networks.
• Understanding cross-layer relationships in these networks is crucial for many research questions.
• Existing generative models often lack the capacity to analyze multiplex network structures effectively.

Purpose of the Study:

• To present a multiplex implementation of the social relations model (SRM).
• To provide accessible tools and tutorials for applying multiplex SRM to diverse datasets.
• To facilitate the broader adoption of generative network modeling in scientific research.

Main Methods:

• Development of a multiplex SRM within the STRAND R package.
• Creation of tutorials for end-user data analysis, parameter visualization, and results interpretation.
• Application of the model to datasets from experimental economics and animal behavior.

Main Results:

• The STRAND R package successfully implements multiplex SRM.
• Worked examples demonstrate practical data analysis and interpretation capabilities.
• The package simplifies the deployment of complex multiplex network models.

Conclusions:

• The multiplex SRM in STRAND R enhances the analysis of multi-layered social networks.
• This tool democratizes the use of advanced network modeling techniques across disciplines.
• It supports research investigating the interplay of different types of social ties and behaviors.