Bibliometrics JACing

I got caught up reading the
Moretti Event
over at The Valve, but I still have a minute to post a few notes about something
I was thinking about earlier today.  I read the introduction to David
Smit’s The End of Composition Studies yesterday; there, he has this to
say about the ideological dissymmetry among compositionists, divergences
characteristic of the field at-large:

Continue reading →

Disappoint-ensity

When a watchful mentor emailed me a link to
Attensity over the
weekend, I was encouraged, finding, from a quick glance at their web site, that
some of the same data-mining they market, as their hallmark, matches up with a few
of the configurations defining a project I have underway. 
Attensity claims to process data and analyze that which is otherwise difficult
to discern.  Their software churns away like some kind of high-powered
heuristic meaning-cruncher–a processor of mass quantities of text into readable
metadata. 

NORA
(non-obvious relationship awareness) for large-scale discourse. 

So I sent them an email inquiring about the whole plot,
all-the-while-recalling that the only other text parser I looked up asked $2k
per year for software licensing.  Did I mention I’m a grad student?

Well, I did mention that in the email to Attensity, the email inquiring about
their project.  And I heard back today–a polite note, something about
serving the US Intelligence community and a starting fee of $50,000. And
something about wishing me the best in my quest.  Thanks.  But no
thank-you. 

The

proliferation of textual analysis
apps self-identifying as the devices built
to root out terrorism piques my interest.  Perhaps because of the sheer
volume of text to be analyzed for particular patterns (suspicious patterns!
watch the parentheticals, Attensity!), mass-discourse text parsers are up and
coming.  And so unbelievably over-priced that they’re no use whatsoever to
the project I’m working on.

Recognize the Non-Obvious

Passed an hour at the public library tonight after an ordered exodus for
house-showing.  There, I picked up Wired Magazine, flipped through a
few pages and learned about this:

NORA:
Non-Obvious Relationship Awareness Software

Among other things, NORA "extends identity recognition with relationship
awareness by detecting both obvious and non-obvious relationships." 
It’s the non-obvious part that intrigues me.  To the extent that it’s
obscure information, how is it discoverable?  It is pitched like the
Sherlock Holmes of software apps bent on digging up the dirt on criminal
associations and long-forgotten debauchery. From SRD’s
site
:

NORA delivers unique Relationship Awareness capabilities.
The unique capabilities of NORA to discern obvious and non-obvious
relationships in real time against streaming data provides a view through up
to 30 degrees of separation that enables an organization to recognize the full
value or threat of an identity.

NORA sends messages to subscribers when it finds something of particular
interest. The gaming industry, for example, uses NORA as a real-time
"trip-wire" to flag high-risk or previously charged cheaters and
alert managers that an individual may pose a potential problem and should be
watched more closely. The levels of protection gaming enterprises gain from
this "trip-wire sensor" reduces the risk, in their case, of fraud.

Thirty degrees, eh?  Damn.  I’m sure I’m connected to some ex-cons
by fewer than thirty separations.  NORA basically infiltrates the
connections with a kind of surveillance, then reports non-obvious associations
for use–I guess–in characterizing prospective employees, scammers, felons,
crooks and plagiarists. But wait, there’s more:

Internally, NORA can reveal employees who:

  • Share the same address with people you’ve arrested.
  • Are related to slip-and-fall victims.
  • You’ve already fired or arrested. […]

With CRM, NORA uncovers:

  • Relationships between highly profitable and less profitable customers.
  • Nature of customer relationships, e.g., family or colleague.
  • The network value of your customers.

Amazing.  And it manages to do all of this (according to SRD’s home
page) "while protecting personal privacy."  How is that,
exactly?   I noticed that "relationship awareness" is
trademarked, and so I don’t want to get into any trouble for bringing this to EWM. 
It’s just that I’m confusing myself by trying to resolve the gap between
"awareness" and "non-obvious."  Maybe that’s where the
"value" element comes in.  The processing of
"non-obvious" into "awareness" is worth something. So
we ought to pilot a program in "non-obvious" studies–unaccredited for
obscurity’s sake, of course.