Scopus data have been used as a source for many types of different bibliometric studies. The different quality properties of Scopus described support different types of analyses.
For instance, there are studies on mobility, using Scopus’ unique historic author-affiliation records, such as by Caroline Wagner and Koen Jonkers on international collaboration, mobility, and openness (Wagner & Jonkers, 2017), funding and collaboration (Leydesdorff, Bornmann, & Wagner, 2019), and author (Pina, Barac, Buljan, Grimaldo, & Marušic, 2019) and institutional (Lee, 2012) collaboration networks. Another example of author-mobility analyses can be found in a bibliometric study to measure knowledge transfer (Aman, 2018). The mobility analysis using Scopus author profiles also informs the research policy of governments, such as through the European Commission’s Joint Research Center (JRC) report on the rise of China as an industrial and innovation powerhouse (Preziosi et al., 2019).
In addition, Scopus’ availability of author first names historically, combined with author profiling, enables studies using author gender assignments: for example, “The gender gap in early-career transitions in the life sciences” (Lerchenmueller & Sorenson, 2018) and “Gender differences in research areas, methods and topics: Can people and thing orientations explain the results?” (Thelwall, Bailey, Tobin, & Bradshaw, 2019). In addition, Scopus author profiles have been used to study the recent phenomenon of hyperprolific authorships (Ioannidis, Klavans, & Boyack, 2018) and for an author database of highly cited researchers (Ioannidis, Baas, Klavans, & Boyack, 2019; Van Noorden & Singh Chawla, 2019).
There are also examples of studies using the full Scopus database to build new algorithms: Richard Klavans and Kevin Boyack developed algorithms on top of the database, resulting in Topics of Prominence (Klavans & Boyack, 2017), which are now prominently displayed in Elsevier’s SciVal research performance product (which uses Scopus data as one of its data sources).
In the more traditional sense of bibliometric analysis, there are many studies available around citation analysis and correlations, such as on the influence of highly cited articles on indicators (Thelwall, 2019; Thelwall & Fairclough, 2015), on correlation between citations and Mendeley readership (Maflahi & Thelwall, 2016; Thelwall & Wilson, 2016), on journal usage (Schloegl & Gorraiz, 2010), and studies revisiting bibliometric laws (Thelwall & Wilson, 2014). Scopus data were also used to analyze initiatives in open science, particularly open access (Solomon, Laakso, & Björk, 2013), citizen science (Follett & Strezov, 2015) and new tools in the scientific space, such as ResearchGate (Thelwall & Kousha, 2017). They have been used to evaluate the fate of rejected manuscripts (Bornmann et al., 2009), to investigate potential citation manipulation by reviewers (Baas & Fennell, 2019; Singh Chawla, 2019) and to study the development of multidisciplinarity (Levitt & Thelwall, 2008). At present, Scopus data are used for bibliometric analysis to inform the EU Open Science Monitor (The Lisbon Council, CWTS, & Esade, 2018).
Another form of common analysis performed using Scopus data is around network visualization and spatial bibliometrics (Bornmann & De Moya Anegón, 2019; Bornmann & Waltman, 2011; Leydesdorff & Persson, 2010; Mutz, Bornmann, de Moya Anegón, & Stefaner, 2014) as well as research building new visualization techniques (Leydesdorff, 2010; Mischo & Schlembach, 2018).