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://dx.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.

Comments

This article was written before Steven Walczak was affiliated with the University of South Florida.

Rights Information

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Was this content written or created while at USF?

false

Citation / Publisher Attribution

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

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