Academic databases are a fundamental source for identifying relevant
literature in a field of study. Scopus contains more than 90 million records and
indexes around 12,000 documents per day. However, this context and the
cumulative nature of science itself make it difficult to selectively identify
information. In addition, academic database search tools are not very intuitive,
and require an iterative and relatively slow process of searching and evaluation.
In response to these challenges, ...
Academic databases are a fundamental source for identifying relevant
literature in a field of study. Scopus contains more than 90 million records and
indexes around 12,000 documents per day. However, this context and the
cumulative nature of science itself make it difficult to selectively identify
information. In addition, academic database search tools are not very intuitive,
and require an iterative and relatively slow process of searching and evaluation.
In response to these challenges, Elsevier has launched Scopus AI, currently in its
Beta version. As the product is still under development, the current user
experience is not representative of the final product. Scopus AI is an artificial
intelligence that generates short synthesis of the documents indexed in the
database, based on instructions or prompts. This study examines the interface
and the main functions of this tool and explores it on the basis of three case
studies. The functional analysis shows that the Scopus AI Beta interface is
intuitive and easy to use. Elsevier's AI tool allows the researcher to obtain an
overview of a problem, as well as to identify authors and approaches, in a more
agile search session than conventional search. Scopus AI Beta is not a substitute
for conventional search in all cases, but it is an accelerator of academic processes.
It is a valuable tool for literature reviews, construction of theoretical
frameworks and verification of relationships between variables, among other
applications that are actually impossible to delimit.
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