Researchers are exploring methods for community detection in hypergraphs, including hyperedge percolation and mutual information maximization. Various approaches are being studied, such as entropy-based models, generative hypergraph models, and spectral embedding. The investigation of hypergraphs also involves analyzing distances, clustering coefficients, and hyper-motifs to better understand complex networks.