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)

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.