NYT Project ‘Cascade’ Strives to Identify the Influencers

One of the two projects/products the New York Times R&D Lab folks talked about at a Huge sponsored meetup last week was something called “Cascade”. (The other was Ricochet.)Cascade

For nearly as long as Twitter has been around, there have been those trying to come up with ways to demonstrate its value.  And not much after that endeavor started, people have been trying to use it as a way to take the pulse of the Internet community.

Tools and more tools abound, promising ways of measuring an individual’s influence (Klout) or a person or company’s impact (Appinions, BrandWatch, Traackr, etc.)

Perhaps one of the holy grails (can that be plural?) for marketers in this grand experiment called “social media” has been finding the influencers — so they in turn can be influenced.

To that end the R&D Group from The New York Times has been working on a project called Cascade. Brandon Melchior @bmelchior, who presented the project, talked about the project’s abilities of seeing how tweets can go viral. (Brandon said you can’t yet find the output from the tool on nytimes.com. But the group is looking to productize it as an API soon.)

The team is taking a feed from Twitter and using it to identify which tweets (e.g. those linking to N.Y. Times articles) get retweeted the most and when. The tweets, visualized as dots in concentric circles, will take off when a key person retweets them (a celebrity, for example.) Certainly, that’s not surprising, so why would someone buy this?

Knowing which influencer to target would be a significant benefit. By studying past data, a marketer might be able to see who Tweeter Zero might be. Who are those people who find my particular subject matter interesting and when they retweet it, others notice?

Such a process still will involve a lot of trial and error, but perhaps it is no different than the process sending out press releases to the journalists who you think will cover you favorably. At least in the Twitter world, there is real data to analyze.

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About Glenn Fannick

Having started on the news side of Dow Jones's corporate products, I've worked in metadata, content and product management roles for Factiva and related products. I was lucky enough to join Dow Jones at a point where the company was expanding along with the Internet's growth. Later I was a leader who was a big part of the growth of Factiva, a successful joint venture of two news rivals -- Dow Jones and Reuters. Factiva became a much more modern, technology focused company than Dow Jones was. We were as much a technology company as a content one. We were early to move our clients off software research tools and to a Web site. We built the first XML platform in our industry. We built innovative APIs and destination products. I lead the effort to build our first Web crawler. I was a key player in embracing text mining based products before anyone was talking about "big data." We moved from the laggard of the industry to the top player. I've always been involved with building online products that leverage world-class content.
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