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What happens if you bring together Jer Thorp, known of many beautiful data representations, and Mark Hansen, UCLA statistics professor and one of the people behind the Moveable Type installation, together at the NYTLabs, which is the research and development lab of The New York Times Company.

Well, you get Cascade [], a 3D interactive visualization tool that reveals how information propagates through social media space by linking the browsing behavior on the NYTimes website with the corresponding social activity in terms of content and URL sharing. In short, the tool aims to reveal the causal factors that determine how tweets about news stories are propagated in the most succesful ways. For instance, the visualization already can demonstrate how viral popularity is mostly influenced by the people who are followed by famous people, who in turn drive a lot of online discussions and retweet activity.

The "side view" shows a 2D bar-graph-like timeline of the activities of a specific story (e.g. shortening of links (blue), tweeting (red), etc.), which can also be explored in 3D, as the radius depicts the time passed since the original news story broke. The yellow sunburst-like "radar view" reveals the separation between individual conversations. The resulting "cascades" can also be further explored to focus only on the most influential tweets (the "backbone of a conversation"), and the specific users who posted them. As a result, the tool is able to display the overall life cycle of a news sharing event, and identify the most influential contributors that drive and influence this cycle.

Also at Nieman Lab.

Tip: the best way to appreciate this visualization, seems to include going through the quick tutorial explanation around the 1-minute mark of the main video, and then to explore several links below the "videos" subtitle, all at the original project page.