Abstract：Metadata categorization for identifying search patterns in a digital library Abstract PurposeFor digital librariesit is useful to understand how users search in a collectionInvestigating search patterns can help them to improve the user interfacecollection management and search algorithmsHoweversearch patterns may vary widely in different parts of a collectionThe purpose of this paper is to demonstrate how to identify these search patterns within a well-curated historical newspaper collection using the existing metadataDesignmethodologyapproachThe authors analyzed search logs combined with metadata records describing the content of the collectionusing this metadata to create subsets in the logs corresponding to different parts of the collectionFindingsThe study shows that faceted search is more prevalent than non-faceted search in terms of number of unique queriestime spentclicks and downloadsDistinct search patterns are observed in different parts of the collectioncorresponding to historical periodsgeographical regions or subject matterOriginalityvalueFirstthis study provides deeper insights into search behavior at a fine granularity in a historical newspaper collectionby the inclusion of the metadata in the analysisSecondit demonstrates how to use metadata categorization as a way to analyze distinct search patterns in a collectionKeywords NewspapersLibrary usersBehaviourDigital librariesCase studiesSearchingArchives Library AutomationAnalyze the users search mode through automated data exploration technologyThis article focuses on studying the user search mode in the digital libraryand uses metadata to analyze to identify these modesThis is basically a process of data explorationwhich combines the search log and the metadata describing the collection content to obtain meaningful results