Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

<Previous Article In Volume
Next Article In Volume>

Analysis of Human Resources Attrition: A Thematic and Sentiment Analysis Approach

Authors
Punamkumar Hinge1, *, Abhijeet Thakur1, Harshal Salunkhe1
1School of Business and Management, Christ University, Bangalore, India
*Corresponding author. Email: punamkumar.hinge@gmail.com
Corresponding Author
Punamkumar Hinge
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_72How to use a DOI?
Keywords
artificial intelligence; employee attrition; prediction model; employee sentiment analysis; thematic analysis; natural language processing
Abstract

In this paper, factors are analyzed for employee attrition to find the main reasons why employees choose to resign and suggested how Artificial Intelligence can be developed to understand and predict future attrition reasons by using thematic and sentiment analysis. The prime objective of study is why people leave the organization and how it can be predicated in advance by using NLP (Natural language processing) AI. Different weights are given for different factors for attrition reasons based on the study conducted for one of the auto-component manufacturing company in Chakan MIDC, Pune, India, high weight factors will be alarming signals for the organizations to be proactive to correct or rectify so that they can avoid attrition. Study can help which valuable employees will leave organization for different reasons in advance. The investigation was done to determine what element had the biggest impact on employee attrition. With the help of the paper, new work policies can be created that benefit both the business organisation and the employee. It might be viewed as a reflection of the employees’ working environments.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
10.2991/978-94-6463-136-4_72
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_72How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Punamkumar Hinge
AU  - Abhijeet Thakur
AU  - Harshal Salunkhe
PY  - 2023
DA  - 2023/05/01
TI  - Analysis of Human Resources Attrition: A Thematic and Sentiment Analysis Approach
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 820
EP  - 828
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_72
DO  - 10.2991/978-94-6463-136-4_72
ID  - Hinge2023
ER  -