Metadata categorization for identifying search patterns in a digital library

Tessel Bogaard*, Laura Hollink, Jan Wielemaker, Jacco van Ossenbruggen, Lynda Hardman

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

Purpose: For digital libraries, it is useful to understand how users search in a collection. Investigating search patterns can help them to improve the user interface, collection management and search algorithms. However, search patterns may vary widely in different parts of a collection. The purpose of this paper is to demonstrate how to identify these search patterns within a well-curated historical newspaper collection using the existing metadata. Design/methodology/approach: The authors analyzed search logs combined with metadata records describing the content of the collection, using this metadata to create subsets in the logs corresponding to different parts of the collection. Findings: The study shows that faceted search is more prevalent than non-faceted search in terms of number of unique queries, time spent, clicks and downloads. Distinct search patterns are observed in different parts of the collection, corresponding to historical periods, geographical regions or subject matter. Originality/value: First, this study provides deeper insights into search behavior at a fine granularity in a historical newspaper collection, by the inclusion of the metadata in the analysis. Second, it demonstrates how to use metadata categorization as a way to analyze distinct search patterns in a collection.

Original languageEnglish
Pages (from-to)270-286
Number of pages17
JournalJournal of Documentation
Volume75
Issue number2
DOIs
Publication statusPublished - 6 Mar 2019

Funding

This research was partially supported by the VRE4EIC project, a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 676247. The computational part of the research has been carried out on the SWISH DataLab software infrastructure developed within the VRE4EIC project (Bogaard et al., 2017). The authors thank the National Library of the Netherlands for providing access to their data and feedback on earlier drafts of this paper.

FundersFunder number
European Union’s Horizon 2020 research and innovation program676247

    Keywords

    • Archives
    • Behaviour
    • Case studies
    • Digital libraries
    • Library users
    • Newspapers
    • Searching

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