Skip to main content

Association rules mining for job seekers' profiles based on Personality traits and Facebook usage

Dr. Agjei, Richard Osei
HIV/AIDS Coordinator, Lecturer, Research Associate and HAESA Patron
  +233556846915
  roagjei@uew.edu.gh
  Download CV

Authors
Olaleye, S & Ukpabi, D & Olawumi, O & Atsa'am, D & Agjei, R & Oyelere, S & Sanusi, I & Agbo, F & Balogun, O & Gbadegeshin, SA & Adegbite, A & Kolog, E.
Publication Year
2022
Article Title
Association rules mining for job seekers' profiles based on Personality traits and Facebook usage
Journal
International Journal of Business Information Systems
Volume
40
Page Numbers
299-326
Abstract

Personality traits play a significant role in many organisational parameters, such as job satisfaction, performance, employability, and leadership for employers. One of the major social networks, the unemployed derives satisfaction from is Facebook. The focus of this article is to introduce association rule mining and demonstrate how it may be applied by employers to unravel the characteristic profiles of the unemployed Facebook users in the recruitment process by employers, for example, recruitment of public relations officers, marketers, and advertisers. Data for this study comprised 3,000 unemployed Facebook users in Nigeria. This study employs association rule mining for mining hidden but interesting and unusual relationships among unemployed Facebook users. The fundamental finding of this study is that employers of labour can adopt association rule mining to unravel job relevant attributes suitable for specific organisational tasks by examining Facebook activities of potential employees. Other managerial and theoretical implications are discussed.

© 2019 University of Education, Winneba