ur society contains all types of organizations, such as companies, research groups and hobby clubs. Affliation networks, as a large and important portion of social networks, consist of individuals and their affiation relations: Two individuals are connected by a link if they belong to the same organization(s). Affliation networks naturally contain many fully connected cliques, since the nodes of the same organization are all connected with each other by de?nition. In this paper, we present methods which facilitate the computation for characterizing the real-world affliation networks of ArXiv coauthorship, IMDB actors collaboration and SourceForge collaboration. We propose a growing hypergraph model with preferential attachment for affliation networks which reproduces the clique structure of af?liation networks. By comparing computational results of our model with measurements of the real-world affliation networks of ArXiv coauthorship, IMDB actors collaboration and SourceForge collaboration, we show that our model captures the fundamental properties including the power-law distributions of group size, group degree, overlapping depth, individual degree and interest-sharing number of real-world affliation networks, and reproduces the properties of high clustering, assortative mixing and short average path length of real-world affliation networks.