Artículos de revistas
Visual text mining: ensuring the presence of relevant studies in systematic literature reviews
Fecha
2015Registro en:
International Journal of Software Engineering and Knowledge Engineering Sciences and Engineering,Singapore : World Scientific Publishing,v. 25, n. 5, p. 909-928, 2015
0218-1940
10.1142/S0218194015500114
Autor
Scannavino, Katia Romero Felizardo
Barbosa, Ellen Francine
Martins, Rafael Messias
Valle, Pedro Henrique Dias
Maldonado, José Carlos
Institución
Resumen
One of the activities associated with the Systematic Literature Review (SLR) process is the
selection review of primary studies. When the researcher faces large volumes of primary studies
to be analyzed, the process used to select studies can be arduous. In a previous experiment, we
conducted a pilot test to compare the performance and accuracy of PhD students in conducting
the selection review activity manually and using Visual Text Mining (VTM) techniques. The
goal of this paper is to describe a replication study involving PhD and Master students. The
replication study uses the same experimental design and materials of the original experiment.
This study also aims to investigate whether the researcher's level of experience with conducting
SLRs and research in general impacts the outcome of the primary study selection step of the
SLR process. The replication results have con¯rmed the outcomes of the original experiment,
i.e., VTM is promising and can improve the performance of the selection review of primary
studies. We also observed that both accuracy and performance increase in function of the
researcher's experience level in conducting SLRs. The use of VTM can indeed be bene¯cial
during the selection review activity.