Workshop

On Wednesday 25 February 2026, we are offering a full-day, pre-conference hands-on workshop focused on cutting-edge bayesian statistical approaches for analysing social networks and social transmission. The workshop is divided into two parts, each taught by researchers who develop and apply those tools:

  • Animal social network analysis with STRAND R package — led by Dr. Daniel Redhead
  • Bayesian network-based diffusion analysis with STbayes R package — led by Dr. Michael Chimento

Practical Information

  • Attendance Fee: €50 (full-day workshop)
  • Capacity: 25 participants
  • Registration: opening soon—first come, first served basis
  • Schedule: 10:00–17:00 (see detailed schedule below)
  • Location: Utrecht University Library, Utrecht Science Park (same venue as the conference)

Part 1 – Workshop on Animal Social Network Analysis (ASNA)

Host: Dr. Daniel Redhead (University of Groningen / MPI EVA)

Overview:

This half-day workshop introduces participants to the current state-of-the-art in Animal Social Network Analysis (ASNA), highlighting recent methodological advances and best practices. Participants will gain a conceptual understanding of key analytical challenges—such as statistical/social dependencies, causal inference, and data-method alignment—and learn how to apply cutting-edge model-based tools to their own research using the STRAND R package. The workshop will combine a lecture, hands-on programming, and opportunities for individual feedback on.

By the end of the workshop, participants will be able to:

  • Identify and avoid some common methodological pitfalls in ASNA (e.g., misuse of permutation tests, ratio indices).
  • Understand how model-based and generative approaches improve inference and interpretability in network analyses.
  • Apply basic causal reasoning using Directed Acyclic Graphs (DAGs) to formulate testable predictions about animal social behaviour.
  • Implement generative network models using the STRAND R package.
  • Discuss how to integrate these approaches into their own datasets and research programs.

Target Audience:

Researchers and students in behavioural ecology, anthropology, and related fields with a basic understanding of R and an interest in network-based approaches to animal behaviour.

Requirements:

Participants should bring a laptop with R and must have the STRAND package installed to participate in the hands-on programming session. Example datasets and scripts will be provided.

About the Host:

Daniel Redhead is an Assistant Professor in the Department of Sociology and the Interuniversity Center for Social Science Theory and Methodology (ICS) at the University of Groningen, and a Guest Researcher at the Max Planck Institute for Evolutionary Anthropology. He received his PhD in Psychology from the University of Essex, following an MA and BA in Anthropology from Durham University. His research sits at the intersection of social network analysis, behavioural ecology, and computational social science. Broadly, his work investigates how networks of cooperation impact the emergence of social and economic inequality within human and animal social systems.

Part 2 – Workshop on Bayesian Models of Social Transmission

Host: Dr. Michael Chimento (University of Zurich / MPI AB)

Overview:

Social transmission is a fundamental consequence of social contact, responsible for the spread of information, behaviour and disease. When analyzing these phenomena, it is important for scientists to be able to 1) identify whether social transmission is present, 2) quantify the relative strength of social transmission versus other intrinsic processes, and 3) ask questions about correlates and pathways of transmission. Over a decade ago, network-based diffusion analysis (NBDA) emerged as a leading framework for understanding the spread of novel behaviours in animal populations, and has been extended several times to include multi-network and dynamic network analyses, time-varying hazards, and varying effects, among other features. Researchers have commonly used a frequentist version of NBDA analyses, largely because there has been no unified Bayesian implementation.

This workshop will introduce participants to the R package “STbayes”, developed by Michael Chimento and Will Hoppitt, which aims to provide a user-friendly pipeline for creating, fitting and interpreting Bayesian models of transmission. The first part of the workshop will be a short review of social transmission and the history and fundamentals of NBDA-type models. The second part of the workshop will be a hands-on tutorial on simulating transmission data, running an analysis pipeline, and understanding the output.

By the end of the workshop, participants will:

  • Learn the history and motivation for the NBDA framework, how this family of models works, and what new extensions to NBDA have been introduced with STbayes.
  • Simulate transmission across networks, and learn how to use this for power analyses.
  • Use STbayes to import data, generate and fit a model, interpret the output, and perform model comparison to test for social transmission.
  • Learn how to integrate STbayes with generative network approaches to carry forward uncertainty in network measurements to inferences about social transmission

Target Audience:

Students and researchers interested in applying network-based analyses to the study of social learning, cultural evolution, and/or collective behaviour.

Requirements:

Participants should bring laptops with 1) RStudio installed, 2) cmdstanr (instructions: https://mc-stan.org/cmdstanr/articles/cmdstanr.html) and 3) STbayes (and its dependencies) installed (instructions: https://github.com/michaelchimento/STbayes/).

About the host:

Michael Chimento is a postdoctoral researcher in the Department of Evolutionary Biology and Environmental Studies at the University of Zurich, and a guest researcher at the Max Planck Institute for Animal Behavior. He received his PhD in Biology from the University of Konstanz, and an MSc from The Evolution of Language & Cognition programme at the University of Edinburgh. He is broadly interested in how individual cognition and social interactions jointly shape how cultures spread, persist and change, and his empirical research uses the great tit (Parus major) and the sulphur-crested cockatoo (Cacatua galerita) as study species for animal culture. He also develops automated methods and analysis tools to study animal cognition and culture.

🕒 Workshop Schedule

Wednesday, 25 February 2026

  • 10:00–12:00: STRAND & Animal Social Network Analysis – Part 1
  • 12:00–12:30: Lunch break
  • 12:30–14:30: STRAND & Animal Social Network Analysis – Part 2
  • 14:30–15:00: Break
  • 15:00–17:00: STbayes & Bayesian Models of Social Transmission

Note: Due to the short lunch break, we recommend that participants bring their own lunch. Alternatively, limited food options (sandwiches/cold meals) are available on campus.