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Article
A Heuristic Text Analytic Approach for Classifying Research Articles
Intelligent Information Management
  • Steven Walczak, University of South Florida
  • Deborah L. Kellogg, University of Colorado Denver
Document Type
Article
Publication Date
1-1-2015
Keywords
  • Bibliometric,
  • Business Analytics,
  • Concept Mining,
  • Heuristic,
  • Research Continuum,
  • Text Analytics,
  • Text Mining
Digital Object Identifier (DOI)
http://doi.org/10.4236/iim.2015.71002
Abstract

Classification of research articles is fundamental to analyze and understand research literature. Underlying concepts from both text analytics and concept mining form a foundation for the development of a quantitative heuristic methodology, the Scale of Theoretical and Applied Research (STAR), for classifying research. STAR demonstrates how concept mining may be used to classify research with respect to its theoretical and applied emphases. This research reports on evaluating the STAR heuristic classifier using the Business Analytics domain, by classifying 774 Business Analytics articles from 23 journals. The results indicate that STAR effectively evaluates overall article content of journals to be consistent with the expert opinion of journal editors with regard to the research type disposition of the respective journals.

Rights Information
Creative Commons Attribution 4.0
Citation / Publisher Attribution

Intelligent Information Management, v. 7, no. 1, p. 7-21

Citation Information
Steven Walczak and Deborah L. Kellogg. "A Heuristic Text Analytic Approach for Classifying Research Articles" Intelligent Information Management Vol. 7 Iss. 1 (2015) p. 7 - 21
Available at: http://works.bepress.com/steven-walczak/6/