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Sökning: WFRF:(Olaleye O) > (2022) > Association rule mi...

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

Olaleye, Sunday Adewale (författare)
School of Business, JAMK University of Applied Sciences, Rajakatu 35, 40100 Jyväskylä, Finland
Ukpabi, Dandison C. (författare)
Jyväskylä School of Business and Economics, University of Jyväskyla, Finland
Olawumi, Olayemi (författare)
School of Computing, University of Eastern Finland, FI-70211 Kuopio, Finland
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Atsa'am, Donald Douglas (författare)
Department of Mathematics Statistics and Computer Science, University of Agriculture, Makurdi, Nigeria
Agjei, Richard O. (författare)
Department of Public Health, University of Central Nicaragua Medical Center, Semaforos del Zumen 3C, Nicaragua
Oyelere, Solomon Sunday (författare)
Luleå tekniska universitet,Datavetenskap
Sanusi, Ismaila Temitayo (författare)
School of Computing, University of Eastern Finland, P.O. Box 111, 80110 Joensuu, Finland
Agbo, Friday Joseph (författare)
School of Computing, University of Eastern Finland, P.O. Box 111, 80110 Joensuu, Finland
Balogun, Oluwafemi Samson (författare)
School of Computing, University of Eastern Finland, FI-70211 Kuopio, Finland
Gbadegeshin, Saheed A. (författare)
Department of Management and Entrepreneurship, Turku School of Economics, University of Turku, Rehtorinpellonkatu 3, FI-20500 Turku, Finland
Adegbite, Ayobami (författare)
Bioenvironmental Science Program, Morgan State University, Baltimore, Maryland, USA
Kolog, Emmanuel Awuni (författare)
Department of Operations and Management Information System, University of Ghana, Accra, Ghana
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 (creator_code:org_t)
InderScience Publishers, 2022
2022
Engelska.
Ingår i: International Journal of Business Information Systems. - : InderScience Publishers. - 1746-0972 .- 1746-0980. ; 40:3, s. 299-326
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

SAMHÄLLSVETENSKAP  -- Medie- och kommunikationsvetenskap -- Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning (hsv//swe)
SOCIAL SCIENCES  -- Media and Communications -- Information Systems, Social aspects (hsv//eng)

Nyckelord

association rule mining
Facebook
unemployment
personality traits
Pervasive Mobile Computing
Distribuerade datorsystem

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

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