Research Article
Text Data Mining of Risk Management Process for Human Resource Management from the Aged Care Quality Reports
@INPROCEEDINGS{10.4108/eai.17-6-2022.2322863, author={Meiting Wu and Yingying Sun and Tao Jiang}, title={Text Data Mining of Risk Management Process for Human Resource Management from the Aged Care Quality Reports}, proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2022}, month={10}, keywords={risk factors human resource management aged care quality reports}, doi={10.4108/eai.17-6-2022.2322863} }- Meiting Wu
Yingying Sun
Tao Jiang
Year: 2022
Text Data Mining of Risk Management Process for Human Resource Management from the Aged Care Quality Reports
ICIDC
EAI
DOI: 10.4108/eai.17-6-2022.2322863
Abstract
This study aimed to compare and test two different research methods for study Australian Aged Care Quality reports to identify risk factors for human resource management. The original 2,876 Aged Care Quality reports were released from March 8, 2015 to December 31, 2018, and they were extracted and loaded into a designed PostgreSQL database. Two typical research methods (‘Pdf(word) advanced search’ and ‘Pdf(word)-text-mining’ based on python) were tested and compared for identifying risk factors from human resource management. Qualitative data analysis was further conducted on these accreditation reports to understand why an RAC home failed in human resource management. There was no significant difference in using different two methods for identify failed Aged Care Quality reports in accuracy. ‘Pdf(word)-text-mining’ has advantages in efficiently analysing structured data and special term in aged care. We found 62 aged care quality reports that recorded failure of at human resource management by ‘Pdf(word)-text-mining’.