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

Year of publication

2022

Authors

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

JAMK University of Applied Sciences

Olaleye Sunday Adewale Orcid -palvelun logo

University of Turku

Gbadegeshin Saheed

University of Jyväskylä

Ukpabi Dandison Orcid -palvelun logo

University of Eastern Finland

Agbo Friday Joseph

Sanusi Ismaila Temitayo

Balogun Oluwafemi Samson

Oyelere Solomon

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Volume

40

Issue

3

Pages

299-326

​Publication forum

58287

​Publication forum level

1

Open access

Open access in the publisher’s service

No

Open access of publication channel

Partially open publication channel

Self-archived

Yes

Other information

Fields of science

Computer and information sciences; Business and management; Media and communications

Keywords

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Publication country

United Kingdom

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes