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.