Twitter mapped all the geotagged tweets since 2009. There’s billions of them, so as you might expect, roads, city centers, and pathways emerge. And it only took 20 lines of R code to make the maps.
Pretty interesting. +1 to take the same maps and compare them with world population to get a sense of geo-biases in twitter data. It’ll probably take a few more than 20 lines to get ‘er done, but it would be a compelling view of any biases that we may see in Twitter!
Too bad they didn’t make the data available! Although I guess that would “go against” their “business model” or something.
So where are those 20 lines of code?
Google ggmap. You’ll find quite a few examples.
Are these maps of geotagged tweets or of geotagging tweeters ? A map of communications or of communicating users ?
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These are my picks for the best of 2015. As usual, they could easily appear in a different order on a different day, and there are projects not on the list that were also excellent.
It’s always tough to pick my favorite visualization projects. Nevertheless, I gave it a go.
I simulated a day for employed Americans to see when and where they work.
We know spending changes when you have more money. Here’s by how much.