An automated approach to identifying search terms for systematic reviews using keyword co-occurrence networks

1. Systematic review, meta-analysis, and other forms of evidence synthesis are critical to strengthen the evidence base concerning conservation issues and to answer ecological and evolutionary questions. Synthesis lags behind the pace of scientific publishing, however, due to time and resource costs which partial automation of evidence synthesis tasks could reduce. Additionally, current methods of retrieving evidence for synthesis are susceptible to bias towards studies with which researchers are familiar. In fields that lack standardized terminology encoded in an ontology, including ecology and evolution, research teams can unintentionally exclude articles from the review by omitting synonymous phrases in their search terms. 2. To combat these problems, we developed a quick, objective, reproducible method for generating search strategies that uses text mining and keyword co-occurrence networks to identify the most important terms for a review. The method reduces bias in search strategy...