Investigating the efficacy of network visualizations for intelligence tasks
There is an increasing requirement for advanced ana-lytical methodologies to help military intelligence analysts cope with the growing amount of data they are saturated with on a daily basis. Specifically, within the context of terror network analysis, one of the largest problems is the transformation of raw tabular data into a visualization that is easily and effectively exploited by intelligence analysts. Currently, the primary method within the intelligence do-main is the node-link visualization, which encodes data sets by de-picting the ties between nodes as lines between objects in a plane. This method, although useful, has limitations when the size and com-plexity of data grows. The matrix offers an alternate perspective because the two dimensions of the matrix are arrayed as an actors x actors matrix. This paper describes an experiment investigating node-link and matrix visualization techniques within social network analysis, and their effectiveness for the intelligence tasks of: 1) iden-tifying leaders and 2) identifying clusters. The sixty participants in the experiment were all Air Force intelligence analysts and we pro-vide recommendations for building visualization tools for this spe-cialized group of users. © 2013 IEEE.
