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Can altmetric mentions predict later citations? A test of validity on data from ResearchGate and three social media platforms

Sumit Kumar Banshal (Computer Science, South Asian University, New Delhi, India)
Vivek Kumar Singh (Computer Science, Banaras Hindu University, Varanasi, India)
Pranab Kumar Muhuri (Computer Science, South Asian University, New Delhi, India)

Online Information Review

ISSN: 1468-4527

Article publication date: 4 January 2021

Issue publication date: 10 May 2021

Abstract

Purpose

The main purpose of this study is to explore and validate the question “whether altmetric mentions can predict citations to scholarly articles”. The paper attempts to explore the nature and degree of correlation between altmetrics (from ResearchGate and three social media platforms) and citations.

Design/methodology/approach

A large size data sample of scholarly articles published from India for the year 2016 is obtained from the Web of Science database and the corresponding altmetric data are obtained from ResearchGate and three social media platforms (Twitter, Facebook and blog through Altmetric.com aggregator). Correlations are computed between early altmetric mentions and later citation counts, for data grouped in different disciplinary groups.

Findings

Results show that the correlation between altmetric mentions and citation counts are positive, but weak. Correlations are relatively higher in the case of data from ResearchGate as compared to the data from the three social media platforms. Further, significant disciplinary differences are observed in the degree of correlations between altmetrics and citations.

Research limitations/implications

The results support the idea that altmetrics do not necessarily reflect the same kind of impact as citations. However, articles that get higher altmetric attention early may actually have a slight citation advantage. Further, altmetrics from academic social networks like ResearchGate are more correlated with citations, as compared to social media platforms.

Originality/value

The paper has novelty in two respects. First, it takes altmetric data for a window of about 1–1.5 years after the article publication and citation counts for a longer citation window of about 3–4 years after the publication of article. Second, it is one of the first studies to analyze data from the ResearchGate platform, a popular academic social network, to understand the type and degree of correlations.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2019-0364

Keywords

Acknowledgements

The authors would like to acknowledge Stacy Konkiel, Director of Research Relations at Digital Science for providing access to data of Altmetric.com.

Citation

Banshal, S.K., Singh, V.K. and Muhuri, P.K. (2021), "Can altmetric mentions predict later citations? A test of validity on data from ResearchGate and three social media platforms", Online Information Review, Vol. 45 No. 3, pp. 517-536. https://doi.org/10.1108/OIR-11-2019-0364

Publisher

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Emerald Publishing Limited

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