  Since 1973 the State Department has been using electronic records systems to
preserve classified communications. Recently, approximately 1.9 million of
these records from 1973-77 have been made available by the U.S. National
Archives. While some of these communication streams have periods witnessing an
acceleration in the rate of transmission; others do not show any notable
patterns in communication intensity. Given the sheer volume of these
communications -- far greater than what had been available until now --
scholars need automated statistical techniques to identify the communications
that warrant closer study. We develop a statistical framework that can
semi-automatically identify from a large corpus of documents a handful that
historians would consider more interesting electronic records. Our approach
brings together related but distinct statistical concepts from nonparametric
signal estimation and statistical hypothesis testing -- which when put together
help us identify and analyze various geometrical aspects of the communication
streams. Dominant periods of heightened and sustained activities aka bursts, as
identified through these methods, correspond well with historical events
recognized by standard reference works on the 1970s.
