Literature Review of Qualitative Data with Natural Language Processing

Abstract

Qualitative research techniques are frequently employed by scholars in the field of social sciences when investigating communities and their communication media. The proliferation of computer-mediated communications has resulted in a substantial volume of textual content. However, the process of coding this vast amount of information necessitates significant time and effort. This article examines the potential for automating specific elements of content analysis through the utilization of natural language processing (NLP) systems, which analyze text in human languages, with a focus on extracting theoretical evidence. In this study, we present a case analysis utilizing NLP to examine the effectiveness of NLP rules in qualitative analysis. Our findings indicate that the NLP rules demonstrated strong performance across multiple codes. The utilization of a NLP system in its current developmental stage has the potential to significantly minimize the text volume, which has to be evaluated using the human coder. This reduction could potentially result in a substantial increase in coding speed, potentially by a factor of ten or more. The research is considered groundbreaking as it pioneers the application of advanced NLP approach to evaluate qualitative data, making it one of the earliest studies in this domain.