This Article Full Text (PDF) All Versions of this Article: 1094428108317202v1 12/3/436    most recent References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Scopus Google Scholar Articles by Janasik, N. Articles by Bruun, H. Social Bookmarking                         What's this?

Text Mining in Qualitative Research

Application of an Unsupervised Learning Method

Helsinki University of Technology, Finland

Timo Honkela

Helsinki University of Technology, Finland

Henrik Bruun

Pieni Kirahvi Oy Ab, Helsinki, Finland

The article provides an introduction to and a demonstration of the self-organizing map (SOM) method for organizational researchers interested in the use of qualitative data. The SOM is a versatile quantitative method very commonly used across many disciplines to analyze large data sets. The outcome of the SOM analysis is a map in which entities are positioned according to similarity. The authors' argument is that text mining using the SOM is particularly effective in improving inference quality within qualitative research. SOM creates multiple well-grounded perspectives on the data and thus improves the quality of the concepts and categories used in the analysis.

Key Words: grounded theory • constructivism • self-organizing map • text mining • document interpretation

This version was published on July 1, 2009

Organizational Research Methods, Vol. 12, No. 3, 436-460 (2009)
DOI: 10.1177/1094428108317202


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?