Abstract
This paper describes NetKit-SRL, or NetKit for short, a toolkit for
learning from and classifying networked data. The toolkit is
open-source and publicly available. It is modular and built for
ease of plug-and-play--such that it is easy to add new modules and
have them interact with other existing modules. Currently available
NetKit modules are focused on ``batch'' within-network learning and
classification: given a partially labeled network, where all nodes and
edges are already known to exist, estimate the class membership
probability of the unlabeled nodes in the network. NetKit has been
used in various network domains such as websites, citation graphs,
movies and social networks.