by KFC, Technology Review
Here’s their conclusion: “Our experiments show that it is possible to estimate ranges of popularity with an overall accuracy of 84% considering only content features.” So before anybody lays eyes on these articles, it’s possible to work out in advance how popular they are likely to become. That’s pretty impressive and may herald important changes in the way articles are written and edited. It’s not hard to imagine an automated article checker–rather like the grammar checkers in word processing programs–that reads articles and predicts how popular they are likely to be when published. In a sense, that’s what journalists do now when they choose topics to write about. But this process is entirely intuitive, based as much on gut feel as on a good understanding of the dynamics of the audience. Huberman’s algorithm could automate this process.
http://www.technologyreview.com/blog/arxiv/27555/?p1=blogs
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