I’m Feeling Lucky: Can Algorithms Better Engineer Serendipity in Research — or in Journalism?
Posted: 7/18/2014 | 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.