5. Conclusions
This paper considered a social network with multiple opinion leader subgroups. It established a very general bounded confidence-based opinion dynamics model for opinion leaders and followers, when the opinion leader subgroups possessed different target opinions. We then utilized a computer simulation technique to investigate the relationship between the proportion of opinion leaders, confidence levels of opinion followers, and degrees of trust of opinion followers toward the opinion leaders. The results provided a quantitative analysis for the collective decision-making of a social group in e-commerce networks. In summary, through the comparative analysis of the three factors, the degrees of trust of opinion followers toward opinion leaders have a more important effect on the influence power of opinion leaders. Thus, in order to maximize the propagation effect in e-commerce, enhancing opinion leaders’ credibility is a crucial precondition. We noted that opinion dynamics research generally uses computer simulation methods to investigate the opinion evolution mechanism for different influence factors. When group opinions evolve in an e-commerce environment, we may use some tools, including Scribe, Chukwa, Kafka, and Flume, to acquire opinion data on social media platforms. Future research lies in using the acquired data to test the degree of approximation between mathematical models and the actual processes of opinion dissemination on social media platforms. Thus, it would help to continuously improve the mathematical model, as well as deepen the understanding of the principle of evolution of public opinion.
