It was developed with the fundamental purpose of specifying the applicability of the so-called "Data Science" and its "Artificial Intelligence" (AI) tools, in the development of qualitative research, applied to the study of complex social phenomena.
The methodology corresponds to the Qualitative Comparative Analysis; for this purpose, data were taken from a qualitative, referential research, developed using the Phenocomplex method, based on Stafford Beer's Viable Systems Models and Van Manen's Hermeneutic Phenomenology. From the Classification, Prediction and Grouping of Data, captured in the anecdotal records of the referential research, it was possible to develop the relational comparison of the findings based on the co-occurrence of phrases and words.
Final Reflections
In a world that is moving rapidly towards the digitalization and virtualization of all its activities, however skeptical one may be of this reality, social researchers find themselves in the imperative need to rethink and take on the challenge of training in the use and efficient application of tools that facilitate Data Science and Artificial Intelligence for the acquisition, processing, analysis and presentation of data related to their studies, both quantitative and qualitative..
Learn how to get the most out of them in order to develop works of greater quality and depth, seeking that at the same time their findings can be more seductive and understandable to the common reader, without losing their validity and scientific reliability, or their academic-practical usefulness..
However, we cannot pretend to completely abandon the practices and procedures of qualitative methods, no matter how complex and burdensome they may be, since they are the ones that allow contact with human reality, with the observed social phenomenon and its complexity..
No machine, software or technology, no matter how sophisticated, will ever be able to replace the capacity for analysis, reflection, abstraction, and adaptation of knowledge, among other faculties inherent to human beings, no matter how impressive the progress achieved to date..
In this sense, Data Science and Artificial Intelligence tools, such as those presented in this article, should be used as guides, or facilitators, for an initial overview of the complex phenomena under study, for the generation of categories and themes of initial analysis, the deepening of aspects or emerging patterns, as well as for the observation of the different edges and relationships necessary to be taken into account in the context of phenomenological complexity, among others: They are then just that, "tools" available to the researcher..