FCS-HGNN's approach can be applied to other types of networks beyond HINs by adapting the model architecture and training process to suit the specific characteristics of different networks. For example, in social networks where relationships between individuals are crucial, the edge semantic attention mechanism can be modified to capture different types of interactions such as friendships, collaborations, or family ties. Additionally, the type-shared feature projection can be adjusted to handle diverse node attributes present in social networks. By customizing these components based on the network structure and data characteristics, FCS-HGNN's methodology can effectively identify communities in various types of networks.