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Evaluation of Research Trends in Knowledge Management: A Hybrid Analysis through Burst Detection and Text Clustering

Author

Listed:
  • Babak Sohrabi

    (Faculty of Management, University of Tehran, Tehran, Iran)

  • Iman Raeesi Vanani

    (Faculty of Management and Accounting, Allameh Tabataba’i University Tehran, Iran)

  • Seyed Mohammad Jafar Jalali

    (Information Technology Management, Allameh Tabataba’i University, Tehran, Iran)

  • Ehsan Abedin

    (Information Technology Management, University of Tehran, Tehran, Iran)

Abstract

This paper aims to analyze the content of validated journal articles related to Knowledge Management (KM) in more than 18,000 papers of the Web of Science (WoS) database and then provide the most recent specific trends in KM field using text mining and burst detection to help researchers invest in the most challenging and fruitful areas of KM research domain. The method for finding the recent trend of KM includes the following steps: Conducting searches and collecting the publication data from WoS; using a hybrid analysis through burst detection and text clustering; also enriching and analyzing the results in order to achieve an overall perspective about the KM position and the popularity among researchers. This study could be valuable for researchers and KM specialists as well as managers as they may study the history of a subject by getting the structure of its scientific productions, so as to purposefully plan and determine the research priorities in KM.

Suggested Citation

  • Babak Sohrabi & Iman Raeesi Vanani & Seyed Mohammad Jafar Jalali & Ehsan Abedin, 2020. "Evaluation of Research Trends in Knowledge Management: A Hybrid Analysis through Burst Detection and Text Clustering," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-27, January.
    • Handle: RePEc:wsi:jikmxx:v:18:y:2020:i:04:n:s0219649219500436
    DOI: 10.1142/S0219649219500436
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