The objective of this article is to illustrate that text mining and qualitative research are epistemologically compatible. First, like many qualitative research approaches, such as grounded theory, text mining encourages open-mindedness and discourages preconceptions. Contrary to the popular belief that text mining is a linear and fully automated procedure, the text miner might add, delete, and revise the initial categories in an iterative fashion. Second, text mining is similar to content analysis, which also aims to extract common themes and threads by counting words. Although both of them utilize computer algorithms, text mining is characterized by its capability of processing natural languages. Last, the criteria of sound text mining adhere to those in qualitative research in terms of consistency and replicability.
Text Mining, Content Analysis, Exploratory Data Analysis, Natural Language Processing, Computational Linguistics, Grounded Theory, Reliability, and Validity
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Recommended APA Citation
Yu, C. H., Jannasch-Pennell, A., & DiGangi, S. (2011). Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability. The Qualitative Report, 16(3), 730-744. Retrieved from https://nsuworks.nova.edu/tqr/vol16/iss3/6