NYTimes science writer Gina Kolata publishes an interesting – and for her, atypical – story Sunday related to content analysis and the integration of statistical and graphic tools.  (See “Enron Offers An Unlikely Boost To E-Mail Surveillance.”)The data under the digital microscope?  One and a half million e-mails sent by the good folks at Enron that were posted to the Web in 2003 by the Federal Energy Regulatory Commission. 

She writes: 

“Scientists had long theorized that tracking the e-mailing and word usage patterns within a group over time - without ever actually reading a single e-mail - could reveal a lot about what that group was up to.  For example, would they be able to find the moment when someone's memos, which were routinely read by a long list of people who never responded, suddenly began generating private responses from some recipients? Could they spot when a new person entered a communications chain, or if old ones were suddenly shut out, and correlate it with something significant?

There may be commercial uses for the same techniques. For example, they may enable advertisers to do word searches on individual e-mail accounts and direct pitches based on word frequency.”

Gee, scientists doing the theorizing?  Advertisers doing word searches?  Might not “tracking the e-mailing and word usage patterns” be a good tool for journalists to think about using?  Are there any journalism departments out there teaching anything about applied content analysis?  It appears so.  At least Mark Miller, formerly of the University of Tennessee, was doing so a decade ago.  And there are some other interesting attempts, here  and here by the Project for Excellence in Journalism.  But it appears nothing as methodologically sophisticated as that carried out by the computer scientists and political scientists is being done by journalists.