Unveiling narratives and representations: AI applied to qualitative data analysis

Abstract

The evaluation of qualitative data represents a fundamental sphere in several disciplines, from social sciences to market research. Deeply interpreting the meanings, contexts, and details underlying qualitative data can uncover valuable insights and inform crucial decisions. With advances in artificial intelligence (AI), promising opportunities arise to improve and streamline this analytical process. Integrating AI into evaluating qualitative data offers a number of advantages. Essentially, AI algorithms can process large volumes of qualitative data quickly and efficiently, allowing researchers to investigate a wide variety of information in a reduced amount of time. However, it is necessary to recognize that AI does not entirely replace human judgment in evaluating qualitative data. This review explores the potentials and limitations of applying artificial intelligence to qualitative data analysis. We will look at how AI algorithms can contribute to identifying patterns, trends and underlying themes in data, as well as discuss the importance of combining computational and qualitative approaches to obtain more comprehensive and meaningful results.