Understanding Recruiters’ Information Seeking Behavior in Talent Search

Mesut Kaya, Toine Bogers

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)


While the rise of online job portals and corporate websites have allowed for easier collection of digital candidate CVs, much of the candidate identification and assessment process—also known as talent search—still requires manual work from recruiters. Recruitment is a professional search domain that has been largely overlooked in IR research, even though better support of recruiters in finding more high-quality candidates could have a big impact on job seekers, companies and society as a whole. Such recruiter support can only be built on top of a more thorough understanding of the information seeking behavior of recruiters when trying to identify the most relevant candidates for open job postings.

In this paper, we present the results of a log-based study of the information seeking process of recruiters at one of Scandinavia’s largest job portals and recruitment agencies. We analyze the behavior of recruiters at different search stages according to the model by Vakkari [24] and distinguish between different types of recruitment tasks. In addition, we contextualize the results of our log analysis using the findings from earlier conducted contextual inquiries to help explain our findings. Our results show that both matching and recruiting talent search is a complex task: recruiters usually submit multiple queries during sessions that can last for hours. We also find that the search behaviour of recruiters during a recruitment task changes over time: recruiters tend to use more filters, formulate longer and more diverse queries, and spend more time assessing candidates near the end of a session than in the beginning. We also observe some differences in search behavior between the different recruitment tasks.
Original languageEnglish
Title of host publicationCHIIR 2023 - Proceedings of the 2023 Conference on Human Information Interaction and Retrieval
Number of pages10
PublisherAssociation for Computing Machinery
Publication date19 Mar 2023
ISBN (Electronic)979-8-4007-0035-4
Publication statusPublished - 19 Mar 2023
EventCHIIR '23: ACM SIGIR Conference on Human Information Interaction and Retrieval - Austin, United States
Duration: 19 Mar 202323 Mar 2023


ConferenceCHIIR '23: ACM SIGIR Conference on Human Information Interaction and Retrieval
Country/TerritoryUnited States
Internet address


  • HR
  • Recruitment
  • information seeking
  • professional search
  • query log analysis


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