Structuring Qualitative Data for Agent-Based Modelling

Amineh Ghorbani,Gerard Dijkema,Noortje Schrauwen

doi:10.18564/jasss.2573

Abstract

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data that was collected through an ethnographic process served as input to the agent-based model. We also used the theoretical analysis performed on the data to define outcome variables for the simulation. We conclude by proposing an initial methodology that describes the use of ethnography in modelling.

Highlights

1.1 Building empirically-grounded artificial societies of agents requires qualitative and quantitative data to inform individual behaviour and reasoning, and document macro level emerging patterns (Robinson et al 2007)
While quantitative data can be collected through surveys, literature and other available sources, gathering qualitative data to design the behaviour of the agents, their decision making process and their forms of interaction is not a straight-forward task (Janssen & Ostrom 2006)
The theoretical analysis that is performed on ethnographic data could be a good source of macro level data for model validation by observing whether the same mechanism and patterns concluded from the analysis result from the simulation (Robinson et al 2007)

Summary

Introduction

1.1 Building empirically-grounded artificial societies of agents requires qualitative and quantitative data to inform individual behaviour and reasoning, and document macro level emerging patterns (Robinson et al 2007). 1.2 Modellers commonly use behavioural and social theories, and desk research to cover the qualitative aspects of agent-based models. They may use surveys and statistical analysis to understand the decision making behaviour of individuals (Sanchez & Lucas 2002; Dia 2002). Ethnography is often exploratory in nature, using observations to construct the analysis from 'bottom-up' Together, this appears to be what is needed for developing agent-based models, in order to characterize the interaction of the individual and the system: Ethnographic research can range from a realist perspective in which behaviour is observed to a constructivist perspective where understanding is socially constructed by the researcher and subjects.

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Conclusion