A New Google News Data Visualization, with Source
migurski writes "For those who liked the Newsmap, this new data visualization experiment focuses on time-based views of Google's news service, showing the ebb and flow of people and places covered, with archives back to February. All source code is available under a Creative Commons license, for those who like to play."
but,what is it for?
... y Dios vio que Linux era bueno... Genesis 99.666
Its got some kind of bug in it..
When you click "mr. Reagan" (hehehe good luck searching, its on Sat. June 19, about 10 blocks from the far right end.
Notice the white thing aprearing top left ??
Hivemind harvest in progress..
I just installed Flashblock on Firefox so I could surf in peace on my old Linux laptop, and now this...
It's interesting enough but doesn't really give you much information - not that I could easily figure out anyway.
It would be nice to see the terms related to each other somehow... like in the hatemap on hatester.
This Like That - fun with words!
I can tell you what it's for: Mindspace tracking. A large number of people read the news every day. Each one of them gathers these little bits of information in some rough proportion to how often they're mentioned, filtered through their level of interest in any given subject.
Say you want to place ads, or make a strategy for getting your message out, or watch a news story explode and see which things get increasing print space over time proportional to how important they are. There you go.
For instance, if this has been the week after Howard Dean's "scream", we would have seen the coverage of that ramp up until it displaced a bunch of issues of much higher world importance.
It's something to think about. This tool seems sort of crude, but it's open source so it could be expanded.
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Play Six Pack Man. I
the google API does not include Google news query rights, so how did they query google news?
Homo Sapiens Americanus--A documentary in p
It is interesting to see Google data displayed this way. Probably most interesting simply because of how this visualization method has been already used for handling other extremely large data sets; DNA microarrays. Just take a look http://www.stanford.edu/group/cyert/