Abstract
AbstractIntroductionOne of the main tasks in information retrieval is the development of Boolean search strategies for systematic searches in bibliographic databases. This includes the identification of free‐text terms and controlled vocabulary. IQWiG has previously implemented its objective approach for search strategy development using a fee‐based text analysis software. However, this implementation is not fully automated, due to a lack of technical options. The aim of our project was to develop a text analysis tool for the development of Boolean search strategies using R.MethodsWe adopt an incremental approach to software development, with the first goal being to develop a minimum viable product for the previously defined use cases. To create an interactive user interface, we use the shiny framework.ResultsOur newly developed shiny app searchbuildR is a text analysis tool with a point‐and‐click user interface, that automatically extracts and ranks terms from titles, abstracts, and MeSH terms of a given test set of PubMed records. It returns searchable, interactive tables of free‐text and MeSH terms. Each free‐text term can also be viewed within its original context in the full titles and abstracts or in a user‐defined word window. In addition, 2‐word combinations are extracted and also provided as an interactive table to help the user identify free‐text term combinations, that can be searched with proximity operators in Boolean searches. The results can be exported to a CSV file. The new implementation with searchbuildR was evaluated by validating the text analysis results against the results of the previously used fee‐based software.ConclusionsQWiG has developed the shiny app searchbuildR to support the development of search strategies in systematic reviews. It is open source and can be used by researchers and other information specialists without extensive R or programming skills. The package code is openly available on GitHub at www.github.com/IQWiG/searchbuildR.
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