Gove, R., Gramsky,, N., Kirby, R., Sefer, E., Sopan, A., Dunne, C., Shneiderman, B. and Taieb-Maimon, M., NetVisia: Heat map & matrix visualization of dynamic social network statistics & content, Proc. IEEE Conference on Social Computing, IEEE Press, Piscataway, NJ (to appear, October 2011).
The Lab for Computational Cultural Dynamics' SOMA Terror Organization Portal (STOP) and social network site for terrorism related analysis and prediction was featured in several major news media. STOP provides methods for reasoning about terror groups and forecasting what they might do in the future. In addition, it contains unique social networking capabilities that allow analysts to effectively cooperate in order to better understand and counteract terror groups.