A new way to review scientific literature is being tested

Mar 19, 2020

HOW DO YOU measure progress? That is the question Kyle Van Houtan, an ecologist at the Monterey Bay Aquarium, in California, found himself asking when he faced the task of working out whether methods of boosting the populations of endangered species in the wild have improved over the years.

In normal circumstances, those keen on studying the effectiveness of research write reviews of the scientific literature. In a flourishing field, though, this may involve reading and extracting information from hundreds, possibly thousands, of papers. That requires a large team, and brings problems of co-ordination. Dr Van Houtan therefore wondered whether getting computers to do the heavy lifting might help.

The answer is that it does. His study on the matter, published this week in Patterns, tapped into a branch of machine learning called natural-language processing. This is a way of analysing large volumes of text with minimal human supervision. He and his colleagues identified five existing natural-language-processing systems and borrowed them. They used them to search the abstracts of 4,313 papers on species-conservation projects published over the course of the past four decades. The software’s task was to look for words associated with success, such as “protect”, “support”, “help”, “benefit” and “growth...


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