A1 Refereed original research article in a scientific journal
Association rule mining for job seekers' profiles based on personality traits and Facebook usage
Authors: Olaleye Sunday Adewale, Ukpabi Dandison C., Olawumi Olayemi, Atsa'am Donald Douglas, Agjei Richard O., Oyelere Solomon Sunday, Sanusi Ismaila Temitayo, Agbo Friday Joseph, Balogun Oluwafemi Samson, Gbadegeshin Saheed A., Adegbite Ayobami, Kolog Emmanuel Awuni
Publisher: Inderscience Publishers
Publication year: 2022
Journal: International Journal of Business Information Systems
Volume: 40
Issue: 3
First page : 299
Last page: 326
eISSN: 1746-0980
DOI: https://doi.org/10.1504/ijbis.2022.124933
Web address : https://doi.org/10.1504/IJBIS.2022.124933
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.