Estimating the Date of First Publication in a Large-Scale Digital Library

Bamman, David; Carney, Michelle Mohr; Gillick, Jon; Hennesy, Cody; Sridhar, Vijitha

doi:10.1109/jcdl.2017.7991569

Cited by 9 publications

(9 citation statements)

References 17 publications

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“…Recent work has sought to better identify duplication in the HathiTrust (Organisciak et al, 2019). Additionally, it has been found that date of first publication can often be inferred from the earliest known duplicate in the HathiTrust (Bamman et al, 2017). This work will inform future iterations of HT+BW, reducing duplication bias and better aligning texts and dates.…”

Section: Discussionmentioning

confidence: 99%

Giving shape to large digital libraries through exploratory data analysis

Organisciak

Schmidt

Downie

2021

Asso for Info Science & Tech

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The emergence of large multi-institutional digital libraries has opened the door to aggregate-level examinations of the published word. Such large-scale analysis offers a new way to pursue traditional problems in the humanities and social sciences, using digital methods to ask routine questions of large corpora. However, inquiry into multiple centuries of books is constrained by the burdens of scale, where statistical inference is technically complex and limited by hurdles to access and flexibility. This work examines the role that exploratory data analysis and visualization tools may play in understanding large bibliographic datasets. We present one such tool, HathiTrust+Bookworm, which allows multi-faceted exploration of the multi-million work HathiTrust Digital Library, and center it in the broader space of scholarly tools for exploratory data analysis.

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Section: Discussionmentioning

confidence: 99%

Giving shape to large digital libraries through exploratory data analysis

Organisciak

Schmidt

Downie

2021

Asso for Info Science & Tech

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“…All books originate in the HathiTrust Digital Library. In order to capture historically representative phenomena, we use the decade-stratified sample of 1,075 books from Bamman et al (2017), in which each decade from 1750-1922 is roughly equally represented. From this sample of 1,075 apparent books, we exclude all non-book records (including digitized newspaper clippings, unbound pamphlets and reports, opera programs, etc.)…”

Section: Datamentioning

confidence: 99%

The Labeled Segmentation of Printed Books

McConnaughey¹,

Dai²,

Bamman

2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

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We introduce the task of book structure labeling: segmenting and assigning a fixed category (such as TABLE OF CONTENTS, PREFACE, INDEX) to the document structure of printed books. We manually annotate the page-level structural categories for a large dataset totaling 294,816 pages in 1,055 books evenly sampled from 1750-1922, and present empirical results comparing the performance of several classes of models. The best-performing model, a bidirectional LSTM with rich features, achieves an overall accuracy of 95.8 and a class-balanced macro F-score of 71.4.

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“…For example, Bamman, Carney, Gillick, Hennesy, and Sridhar (2017) use the text derived from digital surrogates held by HathiTrust to predict the date of first publication of a work. 13 As titles lacking (reliable) publication dates are relatively common during the 19th century, this research allows scholars to make inferences, supported by the words appearing in a text, about an undated volume's likely publication date.…”

Section: Introductionmentioning

confidence: 99%

What Library Digitization Leaves Out: Predicting the Availability of Digital Surrogates of English Novels

Riddell¹,

Bassett²

2021

portal

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Library digitization has made more than a hundred thousand 19th-century English-language books available to the public. Do the books which have been digitized reflect the population of published books? An affirmative answer would allow book and literary historians to use holdings of major digital libraries as proxies for the population of published works, sparing them the labor of collecting a representative sample. We address this question by taking advantage of exhaustive bibliographies of novels published for the first time in the British Isles in 1836 and 1838, identifying which of these novels have at least one digital surrogate in the Internet Archive, HathiTrust, Google Books, and the British Library. We find that digital surrogate availability is not random. Certain kinds of novels, notably novels written by men and novels published in multivolume format, have digital surrogates available at distinctly higher rates than other kinds of novels. As the processes leading to this outcome are unlikely to be isolated to the novel and the late 1830s, these findings suggest that similar patterns will likely be observed during adjacent decades and in other genres of publishing (e.g., non-fiction).

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Estimating the Date of First Publication in a Large-Scale Digital Library

Cited by 9 publications

References 17 publications

Giving shape to large digital libraries through exploratory data analysis

Giving shape to large digital libraries through exploratory data analysis

The Labeled Segmentation of Printed Books

What Library Digitization Leaves Out: Predicting the Availability of Digital Surrogates of English Novels

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