A Social Choice Force Model for Estimating Collective Action Manipulation

For e-commerce websites collective actions have significant influence on the behaviors and decisions of individual customers. In this work, we propose a dynamic utility model for customers in e-commerce by considering a “social choice force” (SCF) effect on utility functions of agents. We apply the Artificial societies, Computational experiments, and Parallel execution (ACP) approach to investigate the short-term efforts of collective action manipulation. Experimental results show that the proposed agent model and algorithm outperform the baseline prediction algorithm and illustrate the effect of collective action manipulation in a group buying directory website.