Similarity of Subjects in Knowledge Management Literature (Using Betweenness Centrality Indicator)

Document Type : Research َ Article

Authors

1 Assistant Professor, Department of Information Science and Knowledge Studies - Yazd University

2 MA. Student of Scientometrics, Yazd Uniersity

Abstract

Purpose: To study the subject structure of knowledge management domain and identify major contributors (domains with the highest number of documents and keywords) through analyzing keywords of Web of Science records.
Methodology: Co-word analysis is used to explore subject structure of knowledge management domain and network analysis to show closeness centrality. Also, the similarity of related domains was calculated using the Jaccard index.
Results: The largest number of high centrality keywords belongs to "Information Systems", followed by "Management" and "Library and Information Science" respectively. The most central keyword in three domains is "Knowledge Sharing". The binary mean index of Jaccard show that "Management" and "Library and Information Science" have the most similarity followed by "Information Systems" and "Library and Information Science".
Conclusion:  Based on results, it is suggested to define Knowledge Management using high centrality keywords, close to Dalkir (2011) definition of the term.

Keywords

References

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History

  • Receive Date: 03 May 2015
  • Revise Date: 09 September 2015
  • Accept Date: 13 September 2015

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