Abstract：Kindlescard catalogsand the future of librariesa collaborative digital humanities project Purpose This paper aims to determine if the digital humanities technique of topic modeling would reveal interesting patterns in a corpus of library-themed literature focused on the future of libraries and pioneer a collaboration model in librarian-led digital humanities projectsBy developing the projectlibrarians learned how to better support digital humanities by actually doing digital humanitiesas well as gaining insight on the variety of approaches taken by researchers and commenters to the idea of the future of librariesDesignmethodologyapproach The researchers collected a corpus of over 150 textsarticlesblog postsbook chapterswebsitesetcthat all addressed the future of the libraryThey ran several instances of latent Dirichlet allocation style topic modeling on the corpus using the programming language ROnce they produced a run in which the topics were cohesive and discretethey produced word-clouds of the words associated with each topicvisualized topics through time and examined in detail the top five documents associated with each topicFindings The research project provided an effective way for librarians to gain practical experience in digital humanities and develop a greater understanding of collaborative workflows in digital humanitiesBy examining a corpus of library-themed literaturethe researchers gained new insight into how the profession grapples with the idea of the future and an appreciation for topic modeling as a form of literature reviewOriginalityvalue Topic modeling a future-themed corpus of library literature is a unique research project and provides a way to support collaboration between library faculty and researchers from outside the libraryRetrieval and IndexingThrough theme modeling technologyresearchers can in-depth discussions on the related literature of the library to provide a form of literature reviewThe study uses theme modeling technologywhich is a form of data explorationwhich is a larger category of machine learningThe purpose of the theme modeling is to extract the hidden theme structure in a large number of filesIn this situationthey use the Latent Dirichlet Allocation method to model the literatureand then find out the future theme of the library