TITLE:
A Heuristic Text Analytic Approach for Classifying Research Articles
AUTHORS:
Steven Walczak, Deborah L. Kellogg
KEYWORDS:
Bibliometric, Business Analytics, Concept Mining, Heuristic, Research Continuum, Text Analytics, Text Mining
JOURNAL NAME:
Intelligent Information Management,
Vol.7 No.1,
January
26,
2015
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.