ABSTRACT
The article outlines an approach to computer modelling called "human simulation,"whose development has been explicitly oriented towards addressing societal problems through transdisciplinary efforts involving stakeholders, change agents, policy professionals, subject matter experts, and computer scientists. It describes the steps involved in the creation and exploration of the "insight space"of policy-oriented artificial societies, which include both analysing societal problems and designing societal solutions. A case study is provided, based on an (ongoing) research project studying "emotional contagion"related to misinformation, stigma, and anxiety in the wake of the COVID-19 pandemic, along with lessons learned about some of the challenges and opportunities facing scientists and stakeholders trying to simulate solutions to complex societal problems. © 2023 F. LeRon Shults.
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 presentation during the SSC 2021 will elaborate on the outcome of implementing the idea. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Today's challenges must be addressed as socio-technical systems, including insights from the social sciences and humanities to adequately represent the human components. As results of simulations are increasingly driving and justifying political and social decisions, it is important to validate and verify (VV) simulation and data. However, the understanding of what establishes truth and how these views impact validation differ between the social and technical partners. Therefore, we must expand our view of VV. The panel provides various use cases and derives ethical questions related to supporting universities during the COVID-19 pandemic, creating multi-disciplinary teams with diverse viewpoints, challenges of using validated insights without critical evaluation, and lack of broadly accepted scientific measures to connect social models and empirical data. We conclude that the role of VV must be reemphasized, that its social-theoretical implications must be better understood, and that it should be driven by an overarching metaethical framework. © 2021 IEEE.