Abstract
Context: Systematic 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. Objective: We 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. Method: We have selected and implemented appropriate visualization techniques into our approach and validated and demonstrated its usefulness in performing real SLRs. Results: The 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. Conclusion: VTM 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.
| Original language | English |
|---|---|
| Pages (from-to) | 1079-1091 |
| Number of pages | 13 |
| Journal | Information and Software Technology |
| Volume | 54 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2012 |
| Externally published | Yes |
Keywords
- Citation document map
- Content document map
- Information visualization
- Systematic Literature Review (SLR)
- Visual Text Mining (VTM)