Abstract
ContextSystematic Literature Reviews (SLRs) are an important component to identify and aggregate research evidence from different empirical studies. Despite its relevance, most of the process is conducted manually, implying additional effort when the Selection Review task is performed and leading to reading all studies under analysis more than once. ObjectiveWe propose an approach based on Visual Text Mining (VTM) techniques to assist the Selection Review task in SLR. It is implemented into a VTM tool (Revis), which is freely available for use. MethodWe have selected and implemented appropriate visualization techniques into our approach and validated and demonstrated its usefulness in performing real SLRs. ResultsThe results have shown that employment of VTM techniques can successfully assist in the Selection Review task, speeding up the entire SLR process in comparison to the conventional approach. ConclusionVTM techniques are valuable tools to be used in the context of selecting studies in the SLR process, prone to speed up some stages of SLRs.
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