A1 Refereed original research article in a scientific journal

Association rule mining for job seekers' profiles based on personality traits and Facebook usage




AuthorsOlaleye 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

PublisherInderscience Publishers

Publication year2022

JournalInternational Journal of Business Information Systems

Volume40

Issue3

First page 299

Last page326

eISSN1746-0980

DOIhttps://doi.org/10.1504/ijbis.2022.124933

Web address https://doi.org/10.1504/IJBIS.2022.124933


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.



Last updated on 2024-26-11 at 13:00