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Quantitative text analysis maxqda12/20/2023 ![]() ![]() A code is a concise qualitative label (eg, “exercise,” “staying healthy,” and “harmful”) to identify the meaning in a segment of text. In this study, we applied both NLP and qualitative text analysis methods to a database of short open-ended survey responses from youth gathered via SMS text messages.Īlthough numerous methods for qualitative text analysis exist, the general approach involves reading the data and assigning codes to text segments. ![]() We conducted a study to compare NLP and qualitative text analysis on the basis of resources used, similarity of findings derived, and the quality of inferences generated. Furthermore, we are aware of no other research that has directly compared qualitative analysis with those augmented with automated NLP approaches for text analysis. Aside from the groundbreaking study of Crowston et al, few methodological researchers have examined NLP through the viewpoint of qualitative analysis. They found that NLP methods performed well in terms of an accurate number of codes identified and a reduction in the amount of text that humans would also have to code they also increased the speed of coding. Crowston et al reported a case study about the use of NLP for qualitative analysis of messages to understand interactions between software teams. However, research examining the methodological merits of NLP techniques is necessary to further consider NLP as a feasible and high-quality approach for qualitative analysis. It allows for the analysis of substantially larger text databases compared with the typical qualitative analysis methods and has been applied to data from electronic health records, PubMed, social media data, and text messages (short message service, SMS). NLP is an area of research and application that explores how computers and automated algorithms can be used to understand and manipulate natural language text to accomplish useful, meaningful tasks. One potential solution to mitigate the resource constraints of qualitative analysis is natural language processing (NLP). However, what if it were possible to analyze larger qualitative databases with sufficient depth while reducing these barriers? Such analysis could leverage the depth of qualitative data with the generalizability of a larger, probabilistic sample. When sample sizes are large, a similar analysis of the entire database may become prohibitive in terms of time and effort, leading researchers to focus on a smaller, purposive subsample. Despite the small sample size, the coding process alone takes considerable time due to the need to read all data, consider meaningful codes, assign relevant codes to segments, and discuss and reach agreement with other analysts. To achieve depth, qualitative sample sizes tend to be small to allow researchers to complete the analysis and gain a detailed understanding. The overarching goal of qualitative research is often to provide an in-depth and nuanced report, typically by writing themes and a rich, thick description that conveys the findings vividly and contextualizes them. For instance, a 30-min interview yields about 10 pages of single-spaced transcribed text. Specifically, text data are dense, and researchers often underestimate the amount of data gathered through qualitative methods. Although the demand for qualitative research is high, it is a relatively labor-intensive process as researchers seek an in-depth understanding. ![]() The process generally involves reading the data, assigning qualitative codes as succinct descriptors of meaning to text segments, and identifying themes that capture the major inferences to address study aims or research questions. Qualitative text analysis is a process of analyzing qualitative text data, such as open-ended survey responses and interview transcripts. ![]() However, text-based data needs different approaches for analysis compared with quantitative data to be able to answer complex research questions. The usual sources of text-based data are open-ended survey items, interview or focus group transcripts, and health record documents. Qualitative data can include images and videos, but text-based data is the most prevalent. Qualitative research methods are increasingly being used in social and health-related research because of their ability to help investigators understand nuances, contexts, and the perspectives of participants in their own words. ![]()
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