Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

Chong Ho Yu, Angel Jannasch-Pennell, Samuel DiGangi

Research output: Contribution to journalArticlepeer-review

127 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)730-744
Number of pages15
JournalQualitative Report
Volume16
Issue number3
StatePublished - May 2011

Keywords

  • Computational Linguistics
  • Content Analysis
  • Exploratory Data Analysis
  • Grounded Theory
  • Natural Language Processing
  • Reliability
  • Text Mining
  • Validity

ASJC Scopus subject areas

  • Social Psychology
  • Cultural Studies
  • Education

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