The NYT Social Media team pulls the curtain back on how Twitter works for them with detailed examples of how changing text and descriptions and focus in their short messages resonated with readers, and which fell flat. Really interesting bit of transparency on their process, and results.
Hollaback and Why Everyone Needs Better Research Methods (And Why All Data Needs Theory), by Zeynep Tufekci:
I’ve taught "introduction to research methods" to undergraduate students for many years, and they would sometimes ask me why they should care about all this "method stuff", besides having a required class for a sociology major out of the way. I would always tell them, without understanding research methods, you cannot understand how to judge what you see.[more inside]
The Hollaback video shows us exactly why.
Visitors to, and other non-residents in, North Korea are now able to tweet and instagram, as mobile data services are gradually opened up. (Probably) the first tweet sent in this way appeared earlier today. [more inside]
The universe (which others call The Twitter) is composed of every word in the English language; Shakespeare's folios, line-by-line-by-line; the Exegesis of Philip K. Dick, exploded; Constantine XI, in 140 character chunks; Sun Tzu's Art of War, in its entirety; the chapter headings of JG Ballard, in abundance; and definitive discographies of Every. Artist. Ever... All this, I repeat, is true, but one hundred forty characters of inalterable wwwtext cannot correspond to any language, no matter how dialectical or rudimentary it may be. [more inside]
Stream graphs, or stacked graphs, are a new form of (sometimes interactive) visualization that present data in a fluid timescale format. For example, the NY Times website has a graph showing the box office receipts from 1996-2008. There's a Twitter streamgraph based on keywords. Here's one of all the musicians a Last.fm user has listened to over time. Track the popularity of baby names back to the 1880s. Possibly the most striking, if not necessarily intuitive, is this visualization of US population by county, 1790-2000. There's already an academic study of the technique.