Using Visualization and Text Mining to Improve Qualitative Analysis

Context: Qualitative analysis is a scientific way to deeply understand qualitative data and to aid in its analysis. However, qualitative analysis is a laborious, time-consuming and subjective process. Aim: The authors propose the use of visualization and text mining to improve the qualitative analysis process. The objective of this paper is to explain how the use of visualization can support the Coding in multiple documents simultaneously, which may allow codes standardization thus making the process more efficient. Method: The Insight tool is being developed to make the proposal feasible and a feasibility study was performed to verify if the proposal offers benefits to the process and improves its results. Results: The study shows that the subjects who applied the proposal got more standardized codes and were more efficient than the ones who applied the process manually. Conclusions: The results derived from the use of visualization and text mining, even in a feasibility study, encourage proceeding with the project, which aims to combine both techniques to obtain more benefits on qualitative analysis conduction.