Do altmetrics correlate with citations? A study based on the 1,000 most-cited articles
| Published date | 18 November 2019 |
| Date | 18 November 2019 |
| DOI | https://doi.org/10.1108/IDD-07-2019-0050 |
| Pages | 192-202 |
| Author | Ali Ouchi,Mohammad Karim Saberi,Nasim Ansari,Leila Hashempour,Alireza Isfandyari-Moghaddam |
| Subject Matter | Library & information science |
Do altmetrics correlate with citations? A study
based on the 1,000 most-cited articles
Ali Ouchi
Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran
Mohammad Karim Saberi and Nasim Ansari
Department of Medical Library and Information Sciences, School of Paramedicine,
Hamadan University of Medical Sciences, Hamadan, Iran
Leila Hashempour
Department of Information Management, Hacettepe University, Ankara, Turkey, and
Alireza Isfandyari-Moghaddam
Department of Knowledge and Information Science, Islamic Azad University, Hamedan Branch, Hamedan, Iran
Abstract
Purpose –The purpose of this paper is to study the presence of highly cited papers of Nature in social media websites and tools. It also tries to
examine the correlation between altmetric and bibliometric indicators.
Design/methodology/approach –This descriptive study was carried out using altmetric indicators. The research sample consisted of 1,000 most-
cited articles in Nature. In February 2019, the bibliographic information of these articles was extracted from the Scopus database. Then, the titles of
all articles were manually searched on Google, and by referring to the article in the journal website and altmetric institution, the data related to
social media presence and altmetric score of articles were collected. The data were analyzed using Microsoft Excel and SPSS.
Findings –According to the results of the study, from 1,000 articles, 989 of them (98.9 per cent) were mentioned at least once in different social
media websites and tools. The most used altmetric source in highly cited articles was Mendeley (98.9 per cent), followed by Citeulike (79.8 per cent)
and Wikipedia (69.4 per cent). Most Tweets, blog posts, Facebook posts, news stories, readers in Mendeley , Citeulike and Connotea and Wikipedia
citations belonged to the article titled “Mastering the game of Go with deep neural networks and tree search”. The highest altmetric score was
3,135 which belonged to this paper. Most tweeters and articles’readers were from the USA. The membership type of the t weeters was public
membership. In terms of fields of study, most readers were PhD students in Agricultural and Biological Sciences. Finally, the results of Spearman’s
Correlation revealed positive significant statistical correlation between all altmetric indicators and received citations of highly cited articles (p-value
= 0.0001).
Practical implications –The results of this study can help researchers, editors and editorial boards of journals better understand the importance
and benefits of using social media and tools to publish articles.
Originality/value –Altmetrics is a relatively new field, and in particular, there are not many studies related to the presence of articles in various
social media until now. Accordingly, in this study, a comprehensive altmetric analysis was carried out on 1000 most-cited articles of one of the
world’s most reliable journals.
Keywords Social media, Bibliometrics, Altmetrics, Nature, Alternative metrics, highly cited articles
Paper type Research paper
Introduction
Today a diverse and rich set of indicators for measuring the
quality of research is emerging from classic metrics to
promising new online ones (Harnad, 2008). Over the years, in
the field of bibliometrics and scientometrics,citation indicators
have been used as one of the most common and important
indicators of the performance appraisal of individuals,
institutions, countries and documents. Citation studies are
based on the opinion that a work that is more cited by other
researchers is more effective, and important scientific output
plays an important role in the formation of ideas and other
researches (Moed and Halevi, 2016;Sudand Thelwall, 2014).
Although these citation-based indicators are among the most
accepted and important indicators for assessing performance
and scientificefficacy, but the great dependence of citation-
based studies on time is one of the mistakes that the scientific
community has always posed (Thelwall et al., 2013), because
citation studies are highly dependent on time, and it takes a
The current issue and full text archive of this journal is available on
Emerald Insight at: www.emeraldinsight.com/2398-6247.htm
Information Discovery and Delivery
47/4 (2019) 192–202
© Emerald Publishing Limited [ISSN 2398-6247]
[DOI 10.1108/IDD-07-2019-0050]
The study was funded by Vice-chancellor for Research and Technology,
Hamadan University of Medical Sciences (No.9712077452).
Received 15 July 2019
Revised 30 August 2019
5 September 2019
Accepted 5 September 2019
192
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