Exploring content-actor paired network data using iterative query refinement with NetLens

Networks have remained a challenge for information retrieval and visualization because of the rich set of tasks that users want to accomplish. This paper demonstrates a tool, NetLens, to explore a content-actor paired network data model. The NetLens interface was designed to allow users to pose a series of elementary queries and iteratively refine visual overviews and sorted lists. This enables the support of complex queries that are traditionally hard to specify in node-link visualizations. NetLens is general and scalable in that it applies to any dataset that can be represented with our abstract content-actor data model