Abstract: This article first summarized the status and problems existing in identifying highly citedpapers, on the basis of which, we assumed that the number of download could be an indicator for identifying highly cited papers. To test the hypothesis, we manually collected 448 749 articles published in 90 core journals between 2004-2016 from the fields of geophysics, computers and automation, mechanics, library and information science, and pharmacy. We depicted the density of downloads and citations of these articles by using statistics. Then, we converted the problem of identifying highly cited papers into a problem of information retrieval, and used the Download Score (DS) and Journal Citation Score (JCS) to score and rank the papers. Finally, precision-recall curve was utilized to analyze and visualize results. Both indicators were proved to be functional to identify highly cited papers, with the DS more effective than JCS.

Key words: Highly cited papers, Precision-recall curve, Download score, Journal citation score, Supplementary indicator