An agent-based approach to modeling online social influence

Abstract

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.