textMap, so so cool – but how does it work?

i am the absolute worst when it comes to methodologies and titles (titles, you probably guessed from these posts).  but it is becoming increasingly apparent that these are at the core of great statistics / information display / research.  take textmap, an engine to analyize the geographic and temporal distribution of news.  it is really quite cool, and something i’ve wanted to do for a while, but it always seemed like there were too many problems to be overcome, before the idea became workable. so i was psyched fo find the site.

-but a problem-

playing with the ‘function of location’ charts has me worried.  montana has a relatively few news sources, and therefore never shows a strong reading.  the east coast, however – particularly the metropolitan corridor – is a sea of red (more news sources in the area).  so, there is variation in both areas, but it isn’t entirely clear what the map is measuring, because comparing across regions is no longer intuitive.  i couldn’t find the methodology on the site (boo!) – and so it isn’t clear what intensity of red indicates.

this isn’t to say the site isn’t worthwhile – the mexico map shows an intuitive trend

Mexico TextMap

but i have to wonder if this is an artifact of paper coverage – why the band between n. florida and s. georgia? – and wonder about coverage in relation to associated thoughts.  (what is the unit of analysis, btw – census tract?)

there is also the old baseline problem: what is the ‘noise’ associated with a given concept (background usage not associated with events)? – and what is the median frequency of ‘related’ terms – its cool if mexico usage went up, but if that was a function of world cup news or a function of immigration news makes a big difference.

hm… actually, with this data set, you could probably look at news conglomeration::variety of media sources, if the answers to above were clear… ooh, shiny.

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