A Bibliometric Analysis and Visualization of Human Resource Big Data Research
Authors: 
Guangda Liu, Renqi Zhu, Bo Li, Lin PanAuthors Info & Claims
Guangda Liu, Renqi Zhu, Bo Li, Lin PanAuthors Info & ClaimsPages 796 - 801
Abstract
The rapid evolution of "Internet Plus" has brought transformative changes to human resources, giving rise to Human Resource Big Data (HRBD). Despite this surge, a research gap exists in HRBD literature, especially in bibliometrics and visualization perspectives. This study aims to fill this void by conducting a meticulous analysis of relevant journal articles. Utilizing the Web of Science database, VOSviewer and CiteSpace software, the researchers examined 192 references, covering aspects such as annual trends, national-level citation frequencies, keyword distributions, highly cited papers, co-authorship patterns, influential journals, and prolific authors. The study contributes to a nuanced understanding of HRBD's current development status and trends, providing valuable insights for professionals navigating the dynamic field of human resources in the era of "Internet Plus."
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Index Terms
- A Bibliometric Analysis and Visualization of Human Resource Big Data Research
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Published In
December 2023
917 pages
ISBN:9798400716669
DOI:10.1145/3659211
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 29 May 2024
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BDEIM 2023
BDEIM 2023: 2023 4th International Conference on Big Data Economy and Information Management
December 8 - 10, 2023
Zhengzhou, China
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