Fred Benenson made this directed graph visualization of conversations about SOPA on Twitter. Check out the full-size 32000x32000 pixel version.
Visualizing common “likes” among Facebook friends, along with instructions on how to make your own visualization of this data with Google Refine and Gephi. (via O’Reilly Radar)
Graph of related ingredients in allrecipe.com’s recipe database. Here’s the study that produced the graphs, and here’s a blog post providing a nice exegesis of the graph: “two main communities fall out, one sweet, the other savory.” (via Food Tech Connect, Hacker News)
Literary Organism, a classic visualization of On the Road by Stefanie Posavec. This post is really just an excuse to link to Stefanie’s portfolio. Everything there is just astounding (including this limited edition of Murakami’s 1Q84).
Talk-o-Meter is an iPhone app that shows how much time in a conversation is taken up by the participants. Right now it seems to work only as a stand-alone app; I would love for this to work with actual phone conversations. Let’s get some deeper metrics in there, too, while we’re at it: when someone calls me, the phone should let me know—based on the caller—how long the conversation is likely to take, what the emotional tenor of the call is likely to be (based on previous sentiment analysis), what topics we’re likely to cover, who I’m most likely to call next, etc.
Language communities of Twitter (European detail) by Eric Fischer on Flickr.
Beautiful maps of language use on Twitter. Via Strange Maps, which has a great write-up.
Dan Zarrella used a simple algorithm to draw a heat map of the optimal link placement for clicks in a tweet. Let’s use analogous technology to find the optimal placement for enjambment in a poem, or the optimal placement for introducing a new character in a novel.
