I'm not up on the current best way to do this, but yes, there are
mechanisms... basically multiple lookups.
Unfortunately, the problem isn't going to just be quantization, but
there will be some skew... for example if you look up my IP you would
think I live in Chimayo when I live in San Ildefonso... the geolocation
can reflect the ISP's registered location which will be skewed toward
the kinds of locations where data centers and/or corporate headquarters
are placed. DSL subscribers may do better than Cable providers but
Microwavers and Satelliters are sure to be skewed. I'm not sure about
Cellular Donglers... but I'm betting everyone using Verizon in NNM is
lumped roughly into one location.
That said, if most of the KSFR folks are streaming from "out of area",
just knowing the general locale (continent, country, state, etc.) might
be enough.
Hopefully someone has done this recently enough to have a formula for
you. My work required "real time" reverse lookup which is marginally
harder than doing it post-data-gathering...
Good luck!
- Steve
Amigos:
I have recently joined the board of our local public radio station,
KSFR <http://ksfr.org/>. Here in Northern New Mexico we have not had
any rating surveys for three-plus years. Consequently, we know very
little about who is listening to what when.
Like most stations these days, we are streaming on the web, and
capturing IP addresses of those listeners. But IP addresses don't
tell us much about listeners and their geography.
Can anyone suggest any tools/apps that will help us tease out more
fine-grained data related to the actual location of our listeners?
Even something down to the county level would be better than what we
now have, but ZIP or census tracts would be the holy grail.
-thanks,
Tom Johnson
--
==========================================
J. T. Johnson
Institute for Analytic Journalism -- Santa Fe, NM USA
505.577.6482(c) 505.473.9646(h)
Twitter: jtjohnson
http://www.jtjohnson.com <http://www.jtjohnson.com/> [email protected]
<mailto:[email protected]>
==========================================
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
