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Articles

Identifying Combinations of Altmetrics and Web of Science Usage That Linked to Early Citations of an Article Received: A Crisp-Set Qualitative Comparative Analysis (csQCA)

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Abstract

The relations of altmetrics/usage of an article and its citations have been studied extensively by using several variable-oriented approaches, e.g., correlations analysis, regression analysis, and so on. Variable-oriented approaches are symmetrically designed to estimate the “net effects” of independent variables on outcomes. In contrast to variable-oriented approaches, Qualitative Comparative Analysis (QCA), a case-oriented approach based on set theory, models the concept of conjunctural causation, rather than a single net effect. QCA assumes asymmetry, equifinality, and causal complexity. In this study, based on four data sets from Scientific Reports, a Crisp-set Qualitative Comparative Analysis (csQCA) was employed to identify combinations of altmetrics and Web of Science usage (WOSusage) that linked to early citations an article received. Our results revealed the existence of diverse combinations of altmetrics and WOSusage that linked to early citations. The four combinations with the highest raw coverage for each data set indicated that high Mendeley readers together with high WOSusage played a key role in early citations an article received. The other altmetrics, including Twitter, Facebook, blogs, and news, played roles in linking to early citations an article received but varied in different combinations for each data set.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant 71704057; China Postdoctoral Science Foundation under Grant 2020M682757; and National Social Science Foundation of China under Grant 18BTQ075. We would like to thank the reviewers for their time spent on reviewing our manuscript and their insightful comments helping us improve the article.

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