Influence identification of opinion leaders in social networks: an agent-based simulation on competing advertisements

Abstract In social networks, factors that influence the spread of information are essential for companies to comprehend. This study uses the opinion dynamic theory to investigate the influence of multiple advertisement opinion leaders in social networks. We construct an integrated bounded confidence model to simulate the evolution of followers’ opinions under two advertisement opinion leaders. Through experimental simulation, we found that the weight of influence on advertisements has a dual effect on the evolution of followers’ opinions, and the probability that information is transmitted by opinion leaders has a significant impact on the evolution of collective opinions. The results show that, for competitive products, companies should properly understand the propaganda power of product advertisements and improve the probability of information being successfully transmitted by opinion leaders.