Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Human behavior modeling within an integrative framework
Human behavior modeling within an integrative framework
Zooming In: Self-Emergence of Movements in New Product Growth
Marketing Science
To agent-based simulation from system dynamics
Proceedings of the Winter Simulation Conference
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The aim of this study is to better understand social influence in online social media. Therefore, we propose a method in which we implement, validate and improve an individual behavior model. The behavior model is based on three fundamental behavioral principles of social influence from the literature: 1) liking, 2) social proof and 3) consistency. We have implemented the model using an agent-based modeling approach. The multi-agent model contains the social network structure, individual behavior parameters and the scenario that are obtained from empirical data. The model is validated by comparing the output of the multi-agent simulation with empirical data. We demonstrate the method by evaluating five versions of behavior models applied to the use case of Twitter behavior about a talent show on Dutch television.