revtools: bibliographic data visualization for evidence synthesis in R

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Authors Martin J Westgate
Journal/Conference Name bioArXiv
Paper Category
Paper Abstract Evidence synthesis (ES) is the process of summarizing scientific information, incorporating a range of methods including systematic reviews, systematic maps, and meta-analyses. ES is critical for translating scientific information into recommendations for management or policy, but is becoming increasingly challenging due to rapid growth in publication of scientific literature. From a computational perspective, the ES process can be viewed as a sequence of operations on bibliographic data, including importing, de-duplicating, and classifying large numbers of articles or reports. These are common tasks in natural language processing and machine learning, yet few software tools are available to help researchers access these techniques for manipulating bibliographic data in a systematic way. Here, I present revtools, an R package for exploratory investigation of bibliographic data during reviews and evidence syntheses. It provides tools for the import and de-duplication of bibliographic data formats, and cluster analysis and visualization of article titles, abstracts and keywords using topics models. The key function of revtools is an interactive viewer window that allows users to view and select and export the articles, terms or topics most relevant to their study. Rather than generating lists of text commonly provided by other article sorting software, revtools displays this content as points in an ordination cloud, allowing rapid, intuitive assessment of patterns within the corpus. These tools will assist users to identify key topics and outlying articles or terms, increasing the navigability and ease of processing of bibliographic datasets.
Date of publication 2018
Code Programming Language R
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