Deakin University
Browse

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

Version 2 2024-06-12, 15:37
Version 1 2023-02-28, 00:59
journal contribution
posted on 2024-06-12, 15:37 authored by B Sohrabi, IR Vanani, SMJ Jalali, E Abedin
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.

History

Journal

Journal of Information and Knowledge Management

Volume

18

Pagination

1950043-1950043

ISSN

0219-6492

eISSN

1793-6926

Language

en

Publication classification

C1 Refereed article in a scholarly journal

Issue

4

Publisher

World Scientific Pub Co Pte Lt

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC