Open AccessCompatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability
Author(s) -
Chong Ho Yu,
Angel Jannasch-Pennell,
Samuel DiGangi
Publication year - 2014
Publication title -
the qualitative report
Language(s) - English
Resource type - Journals
ISSN - 2160-3715
DOI - 10.46743/2160-3715/2011.1085
Subject(s) - grounded theory , computer science , consistency (knowledge bases) , qualitative research , reliability (semiconductor) , content analysis , natural language processing , data science , qualitative analysis , information retrieval , text mining , artificial intelligence , social science , sociology , power (physics) , physics , quantum mechanics
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.