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Beyond Job Listings: Enhancing Job Recommendation System: Ledigajobb.se as case-study
Umeå University, Faculty of Social Sciences, Department of Informatics.
2024 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Online job platforms play a vital role in connecting job seekers with relevant opportunities. However, the effectiveness of these platforms hinges on the sophistication of their recommendation systems. While technical metrics provide valuable insight, there is a notable gap in the literature concerning the user experience (UX) of job recommendations systems. Job platforms often overlook how users interact with and perceive these systems beyond the accuracy of recommendations. This study aims to fill this gap by answering the research question, how can the recommendation system on online job platforms be enhanced to surpass traditional job listings, offering users more personalized and effective job matches? Partnering with a prominent job platform, Ledigajobb.se, the author employed a mixed-methods approach, including surveys and focus groups. The study reveals users’ openness to new career avenues, the importance of transparent communication, and concerns regarding platform accessibility and recruitment processes. The study contributes to job recommendation systems research that aligns more closely with user experience and expectations by adding empirical data and actionable insights for enhancing job recommendation platform performance and job seeker satisfaction.

Place, publisher, year, edition, pages
2024. , p. 34
Series
Informatik Student Paper Master (INFSPM) ; 2024.15
Keywords [en]
Recommendation Systems, Job Matching, User Experience, Personalization in Job Searches, Ledigajobb.se.
National Category
Social Sciences Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:umu:diva-227496OAI: oai:DiVA.org:umu-227496DiVA, id: diva2:1879725
External cooperation
Ledigajobb.se
Educational program
Master's Programme in Human-Computer Interaction
Supervisors
Examiners
Available from: 2024-08-05 Created: 2024-06-28 Last updated: 2025-02-17Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf