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Objective: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. Materials and Methods: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses (n=250) and assess whether CoCites retrieves all eligible articles while screening fewer titles. Results: CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. Discussion: CoCites uses the expert knowledge of authors to rank related articles. The method does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible. Conclusion: CoCites is an efficient and accurate method for finding relevant related articles.
This is a preprint submission to PeerJ Preprints. The authors welcome feedback.
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