Advancing Automated Content Analysis in Knowledge Management Research: The Use of Compound Concepts

Nora Fteimi, Dirk Basten, F. Lehner
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引用次数: 3

Abstract

This article reports on the development of a knowledge management (KM) dictionary and its application to automated content analysis to investigate topical foci of KM publications and provide an overview of the current research landscape. While automated content analysis gains importance, a problem prevails concerning the use and analysis of compound concepts (e.g., organizational learning). Using a self-developed dictionary of KM-related compound concepts, a sample of 4,290 publications from ten top-ranked KM journals and one KM conference was analyzed using text-mining software. Based on the dictionary approach, this study investigates core research themes of the KM discipline and compares key research interests throughout the IJKM community and those of other outlets. The investigation provides guidance to identify research opportunities in KM and provides useful implications concerning the application of dictionaries. Practitioners might adapt their organizations' approaches to KM accordingly, with regard to prevailing themes and trends in KM research.
在知识管理研究中推进自动化内容分析:复合概念的使用
本文报告了知识管理(KM)词典的开发及其在自动内容分析中的应用,以调查KM出版物的主题焦点,并概述了当前的研究前景。当自动化内容分析变得越来越重要的时候,一个关于复合概念的使用和分析(例如,组织学习)的问题盛行。使用自主开发的KM相关复合概念词典,使用文本挖掘软件分析了来自10个顶级KM期刊和一个KM会议的4290篇论文样本。基于词典方法,本研究调查了KM学科的核心研究主题,并比较了整个IJKM社区和其他渠道的关键研究兴趣。调查提供了指导,以确定研究机会在KM和提供有用的启示有关词典的应用。实践者可能会根据知识管理研究中的流行主题和趋势,相应地调整他们组织的知识管理方法。
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