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Research@WUR
Article . 2021
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Information and Software Technology
Article . 2021 . Peer-reviewed
License: Elsevier TDM
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Automation of systematic literature reviews: A systematic literature review

Authors: van Dinter, Raymon; Tekinerdogan, Bedir; Catal, Cagatay;

Automation of systematic literature reviews: A systematic literature review

Abstract

Abstract Context Systematic Literature Review (SLR) studies aim to identify relevant primary papers, extract the required data, analyze, and synthesize results to gain further and broader insight into the investigated domain. Multiple SLR studies have been conducted in several domains, such as software engineering, medicine, and pharmacy. Conducting an SLR is a time-consuming, laborious, and costly effort. As such, several researchers developed different techniques to automate the SLR process. However, a systematic overview of the current state-of-the-art in SLR automation seems to be lacking. Objective This study aims to collect and synthesize the studies that focus on the automation of SLR to pave the way for further research. Method A systematic literature review is conducted on published primary studies on the automation of SLR studies, in which 41 primary studies have been analyzed. Results This SLR identifies the objectives of automation studies, application domains, automated steps of the SLR, automation techniques, and challenges and solution directions. Conclusion According to our study, the leading automated step is the Selection of Primary Studies. Although many studies have provided automation approaches for systematic literature reviews, no study has been found to apply automation techniques in the planning and reporting phase. Further research is needed to support the automation of the other activities of the SLR process.

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Keywords

Automation, Text mining, Natural language processing, Machine learning, Review, Systematic literature review (SLR)

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    254
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
254
Top 0.1%
Top 1%
Top 0.1%
Green
bronze