Our research teams have three chapters published in the new volume in the Springer Proceedings in Complexity series: Advances in Social Simulation. I’ve given the abstracts of each and a link to our chapters below.

The first chapter was led by Pati Antosz: “Documenting Data Use in a Model of Pandemic ‘Emotional Contagion’ using the Rigour and Transparency Reporting Standard.” The chapter can be downloaded here.

Abstract: “This paper utilizes the recently developed Rigour and Transparency Reporting Standard as a framework for describing aspects of the use of data in an agent-based modelling (ABM) EmotiCon project studying emotional contagion during the COVID-19 pandemic. After briefly summarizing the role of the ABM in the wider EmotiCon project, we outline how we intend to utilize qualitative data from a natural language processing analysis of Twitter data and quantitative data from a nationally representative survey in model building.”

The second chapter was led by Ivan Puga-Gonzalez: “Generation Gaps: An Agent-Based model of Opinion Shifts among Cohorts.” The chapter can be downloaded here.

Abstract: “This paper presents the findings of an agent-based model of the shift toward liberal opinions over time within contemporary European populations. Empirical findings and theoretical reflection on this sort of shift suggest that cohort effects, and especially changes in the opinions of teenagers, are a primary driver of liberalization at the population level. We outline the core features and dynamics of the model and report on several optimization experiments that clarify the conditions under which – and the mechanisms by which – opinions be-come more liberal as agents interact with one another within and across cohorts.”

The third chapter is led by Themis Xanthopoulou: “The Problem with Bullying: Lessons Learned from Modelling Marginalization with Diverse Stakeholders.” The chapter can be downloaded here.

Abstract: “While building a simulation model to gain insights on bullying interventions, we encountered challenging issues that forced us to reconsider our modelling concepts. We learned lessons about the need for quality assurance and a more demanding construction process when building models that aim to support decision making. One of the lessons is that even academically accepted concepts such as ‘bullying’ can be ambiguous. Experts and interested parties do not agree about how to define and use the term bullying. Indeed, before we can model ‘bullying’, we need a shared understanding of its meaning. Otherwise, insights from the model could be misinterpreted and lead to misleading conclusions. Concepts are inherently imprecise and contain grey areas. Although this may be true, not all of them are ambiguous. For the scope of this paper, ambiguity implies that the same word is used to point to different concepts. For different reasons, bullying has evolved to point to different concepts for different people and sometimes even for the same person. We propose to solve these challenges by identifying which concrete bullying behaviors to target, and by focusing on simulation models for interventions addressing those behaviors.”