When Don Thorson and Charlie Constantini looked at the social graph – some 1 billlion connected people all sharing information at an incredibly fast pace – they saw a problem, and an opportunity. Data extraction wasn’t playing as big a role in the picture as it could, so the possibility that all those connected users out there could actually be gaining knowledge proportional to the size of the social network wasn’t being realized. How to return more value to end users? Thorson, whose career has spanned the video game, computer, Internet and communications industries and companies including Atari, Apple, Netscape, and Ribbit, says there had to be a way to “unlock what the world thinks about everything with the optimistic view that all of us are smarter than any of us.”

So was Swipp born. The startup – co-founded by CEO Thorson, Chief Swipp officer Constantini, and CTO Ramani “Nara” Narayan (both also Ribbit veterans) – and its new social intelligence platform launched yesterday. Its aim is to extract the wisdom of the crowd in a global, aggregated way with a solid data structure foundation as its starting point. Swipp’s effort to merge the worlds of social tools and knowledge tools is based on organizing data around terms or topics in what Thorson calls a “pure data” approach – not an interpreted or extracted one – allowing for data to be aggregated, displayed, and archived around a specific person, place, or thing.

So, when a consumer “swipps” – enters a topic via the web or a mobile device, adds a comment about it, and scores it so that their rating becomes part of the Swipp Index (its stock index of social intelligence) – he or she gets what Constantini calls a “one-two punch of what the world is saying and the truth.” That is, you get to see what people are saying socially about that exact topic, and the Index, which is the combined social data for each topic that can be sorted by geography, time, gender, and age. For the reference knowledge and the context behind millions of topics, Swipp leverages Freebase and its entity graph of people, places and things.

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New Career Opportunities Daily: The best jobs in media.

Derrick Harris of GigaOM reports, “When it comes to using data to determine how to build a team or manage a game, the National Football League appears years behind its professional sports brethren such as Major League Baseball and the National Basketball Association. But perhaps the increasing popularity of machine learning can change that by helping NFL teams make more sense of their very complex datasets. Delving deep into the world of computer science might sound like overkill, but professional football is big business in America, and an analytic edge off the field might be just as important as athletic or strategic edges on the field. Heck, it might help create them.” continued…

New Career Opportunities Daily: The best jobs in media.

New Career Opportunities Daily: The best jobs in media.

New Career Opportunities Daily: The best jobs in media.