Saoud, Bilal2024-03-122024-03-122021-05-25978-9931-9788-0-0http://dspace.univ-oeb.dz:4000/handle/123456789/18727Complex networks have in generally communities. These communities are very important. Network’s communities represent sets of nodes, which are very connected. In this research, we developed a new method to find the community structure in networks. Our method is based on flower pollination algorithm (FPA) witch is used in the splitting process. The splitting of networks in our method maximizes a function of quality called modularity. We provide a general framework for implementing our new method to find community structure in networks. We present the effectiveness of our method by comparison with some known methods on computer-generated and real-world networks.enCommunity detection; networks; flower pollination algorithm; normalized mutual information; modularityModularity maximization to find community structure in complex networksArticle