ERIC Number: EJ1467982
Record Type: Journal
Publication Date: 2025
Pages: 16
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1545-679X
Available Date: 0000-00-00
Teaching Case: Leveraging Topic Modeling to Predict and Prevent Employee Attrition
Frank Lee; Alex Algarra
Information Systems Education Journal, v23 n4 p69-84 2025
This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop predictive models to forecast employee churn, empowering organizations to proactively implement retention strategies.
Descriptors: Labor Turnover, Data Analysis, Natural Language Processing, Employees, Prediction, Models, Assignments
Information Systems and Computing Academic Professionals. Box 488, Wrightsville Beach, NC 28480. e-mail: publisher@isedj.org; Web site: http://isedj.org
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A