I’m Feeling Lucky: Can Algorithms Better Engineer Serendipity in Research — or in Journalism?

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By: Liam Andrew | Nieman Journalism Lab

Let’s say you have a research topic, and maybe even an angle. You dive in by reading the canonical classics, all of which seem to cite one other, and maybe some of the most recent debates. Now what? Or perhaps you’ve been studying the same topic for years and feel stuck. How can you find a fresh take on a stale debate?

By this point, you might have exhausted the help that discovery platforms like Google and Facebook can provide. Google will reveal the most-cited works (especially on the more specialized Google Scholar or Google News), and Facebook might yield the ones your friends or subject experts value — but there’s no easy way to break out of the networks that define these platforms. Libraries provide content-based discovery portals, which offer one way out, but they often give you too much to wade through, with clunky interfaces and varying levels of relevance.

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