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

Author

Listed:
  • Sunday Adewale Olaleye
  • Dandison C. Ukpabi
  • Olayemi Olawumi
  • Donald Douglas Atsa'am
  • Richard O. Agjei
  • Solomon Sunday Oyelere
  • Ismaila Temitayo Sanusi
  • Friday Joseph Agbo
  • Oluwafemi Samson Balogun
  • Saheed A. Gbadegeshin
  • Ayobami Adegbite
  • Emmanuel Awuni Kolog

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.

Suggested Citation

  • Sunday Adewale Olaleye & Dandison C. Ukpabi & Olayemi Olawumi & Donald Douglas Atsa'am & Richard O. Agjei & Solomon Sunday Oyelere & Ismaila Temitayo Sanusi & Friday Joseph Agbo & Oluwafemi Samson Bal, 2022. "Association rule mining for job seekers' profiles based on personality traits and Facebook usage," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 40(3), pages 299-326.
    • Handle: RePEc:ids:ijbisy:v:40:y:2022:i:3:p:299-326
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