Dr Mohammad Hossein Nekoofar
Immediate Past President of Iranian Association of Endodontists
Director of International Relations, Tehran University of Medical Sciences
Honorary Senior Clinical Lecturer, Cardiff University

Science Map of Cochrane Systematic Reviews Receiving the Most Altmetric Attention Score: A Network Analysis


Abstract

The present study aimed to analyze and visualize the science map of Cochrane systematic reviews (CSRs) with high Altmetric attention score (AAS). On 2020-07-29, the altmetric data of the Cochrane Database of Systematic Reviews were obtained from the Altmetric database (Altmetric LLP, London, UK). Bibliometric data of the top 5% AAS of CSRs were extracted from the Web of Science. Keyword co-occurrence, co-authorship   and   co-citation   network   analyses   were   then   employed   using   VOSviewer software. The random forest model was used to rank the importance of the altmetric resource. A total of 11222 CSRs with AAS were found (Total mentions: 305265), with Twitter being the most popular Altmetric resource. Consequently, the top 5% AAS (649 articles, mean AAS: 204.95, 95% confidence level: 18.95, mean citations:  123.68, 95% confidence level: 13.9) were included. Density mapping revealed female, adult and child as the most popular author keywords. According to network visualization, Helen V. Worthington (University of Manchester, Manchester, UK), the University of Oxford and UK had the greatest impact on the network at the author, organization and country levels respectively. AAS were weekly correlated with citations (rs=0.21) although citations were moderately correlated with policy document and blog mentions (rs=0.46 and rs=0.43). Cochrane systematic reviews received high levels of online attention, particularly in the Twittersphere and mostly from the UK. However, CSRs were rarely publicized and discussed using recently developed academic tools, such as F1000 prime, Publons and PubPeer.

Keywords: Cochrane systematic review, Altmetric, Bibliometric, Twitter, Machine learning, Network analysis, Random forest

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