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The New York Times’ R&D Lab has built a tool that explores the life stories take in the social space » Nieman Journalism Lab
And it can assess the link-level impact of individual users. Who are the people, exactly, who drive other people to tweet about a link? That impact isn’t just a function of follower counts; in fact, often, the most-followed people don’t generate many retweets — possibly because their followers assume others have already seen the link. Project Cascade’s findings so far suggest, though, that it’s the people who are followed by the famous people who can drive a lot of retweet activity and drive discussions — “the deep, hidden influencers,” Zimbalist calls them, who can help news content have impact.

“These aren’t the kinds of things you would have seen in spreadsheets,” Porway notes. Static representations like spreadsheets don’t demonstrate well the human connections behind content-sharing the way that a visualized, animated universe can. With a 3D representation of interaction, you can see how interest groups — both ad hoc and ongoing, weak-tied and strong — form around particular pieces, and varieties, of content. ”What we’re already beginning to see here,” Zimbalist says, “is these different clusters of people in these different vertical areas who are always out there talking about our content.”
data  nytimes  twitter  visualization  invisible  hidden 
september 2011 by jenlowe

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