Researchers are using a kind of machine learning known as sentiment analysis to assess the successes and failures of wildlife conservation over time. In their study, appearing March 19 in Patterns—a new open access data science journal from Cell Press—the researchers assessed the abstracts of more than 4,000 studies of species reintroduction across four decades and found that, generally speaking, we’re getting better and better at reintroducing species to the wild. They say that machine learning could be used in this field and others to identify the best techniques and solutions from among the ever-growing volume of scientific research.
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