Application of the Ant Colony Optimization Algorithm to the Influence-Maximization Problem

Consumers often form complex social networks based on a multitude of different relations and interactions. These interactions influence the decisions they make about adopting products or behaviors, and hence a company could receive a large cascade of further recommendations if it can identify and target influential consumers. This research borrowed from swarm intelligence—specifically the ant colony optimization algorithm—to address the influence- maximization problem. The proposed approaches were evaluated using a coauthorship data set from the arXiv e-print (www.arxiv.org), and the obtained experimental results demonstrated that our approaches outperform two well-known benchmark heuristics.