Predicting article citations using data of 100 top-cited publications in the journal Medicine since 2011: A bibliometric analysis.

ABSTRACT:

Background

Publications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to

SUBMITTER: Kuo YC 

PROVIDER: S-EPMC7598835 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature