KeyGraph-based chance discovery for exploring the development of e-commerce topics

Liang-Chu Chen (), Ting-Jung Yu () and Chia-Jung Hsieh ()
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Liang-Chu Chen: National Defense University
Ting-Jung Yu: National Defense University
Chia-Jung Hsieh: National Defense University

Scientometrics, 2013, vol. 95, issue 1, No 18, 257-275

Abstract: Abstract The purpose of this study is to integrate the method of chance discovery with visualization tools (KeyGraph) for presenting important and latent research topics in the e-commerce (EC) field. This study collects keywords and abstracts from 995 articles in four primary EC journals. To establish the professional terms of EC, this work divides EC development into three periods: the development of the Internet, the growth of information technology, and the extension of commerce applications. For exploring significant and latent EC topics, this study analyzes the differences and similarities between international and Taiwanese sources. Pursuing this approach yields three findings. First, this paper determines that the KeyGraph as a computing process and a visualization tool is an effective method for exploring future research topics. Second, international EC topics have different thematic characteristics at different phases and they are more diverse and extensive than Taiwanese sources. Third, a professional thesaurus is very helpful in identifying EC research topics. All these findings suggest Taiwanese scholars should pay more attention to research issues from international journals when studying EC.

Keywords: Chance discovery; KeyGraph; Electronic commerce; Text mining (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11192-012-0826-2

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