Knowledge transfer in agent-based computational social science

This article addresses knowledge transfer dynamics in agent-based computational social science. The goal of the text is twofold. First, it describes the tensions arising from the convergence of different disciplinary traditions in the emergence of this new area of study and, second, it shows how these tensions are dealt with through the articulation of distinctive practices of knowledge production and transmission. To achieve this goal, three major instances of knowledge transfer dynamics in agent-based computational social science are analysed. The first instance is the emergence of the research field. Relations of knowledge transfer and cross-fertilisation between agent-based computational social science and wider and more established disciplinary areas: complexity science, computational science and social science, are discussed. The second instance is the approach to scientific modelling in the field. It is shown how the practice of agent-based modelling is affected by the conflicting coexistence of shared methodological commitments transferred from both empirical and formal disciplines. Lastly, the third instance pertains internal practices of knowledge production and transmission. Through the discussion of these practices, the tensions arising from converging dissimilar disciplinary traditions in agent-based computational social science are highlighted. © 2018 Elsevier Ltd

• Fecha de publicación: 2019
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: eng
• OAI Identifier: oai:repository.urosario.edu.co:10336/23349
• Acceso en línea: https://doi.org/10.1016/j.shpsa.2018.05.001; https://repository.urosario.edu.co/handle/10336/23349
• Palabra clave: Article; Cross fertilization; Human; Simulation; Sociology; Tension; Agent-based modelling; Complexity science; Discipline-building; Interdisciplinarity; Scientific models; Social simulation
• License: Abierto (Texto Completo)