Association for Computing Machinery
Network sampling is integral to the analysis of social, information, and biological networks. Since many real-world networks are massive in size, continuously evolving, and/or distributed in nature, the network structure is often sampled in order to facilitate study. For these reasons, a more thorough and complete understanding of network sampling is critical to support the field of network science. In this paper, the authors outline a framework for the general problem of network sampling, by highlighting the different objectives, population and units of interest, and classes of network sampling methods.