| Summary: | Abstract— Background: A systematic literature review (SLR)
is a methodology used to aggregate all relevant existing
evidence to answer a research question of interest. Although
crucial, the process used to select primary studies can be
arduous, time consuming, and must often be conducted
manually. Objective: We propose a novel approach, known as
‘Systematic Literature Review based on Visual Text Mining’
or simply SLR-VTM, to support the primary study selection
activity using visual text mining (VTM) techniques. Method:
We conducted a case study to compare the performance and
effectiveness of four doctoral students in selecting primary
studies manually and using the SLR-VTM approach. To
enable the comparison, we also developed a VTM tool that
implemented our approach. We hypothesized that students
using SLR-VTM would present improved selection performance and effectiveness. Results: Our results show that incorporating VTM in the SLR study selection activity reduced the time spent in this activity and also increased the number of studies correctly included. Conclusions: Our pilot case study presents promising results suggesting that the use of VTM may indeed be beneficial during the study selection activity when performing an SLR.
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