Missing Data, Speculative Reading

Bibliographic Data

ID21245486
AuthorsRebecca Sutton Koeser (0000-0002-8762-8057, Princeton University), Zoe Leblanc (0000-0003-2012-8805, University of Illinois Urbana-Champaign)
Year2024
Volume9
Issue2
Publication date2024-05-29
Open AccessYes
TypeARTICLE
VenueJournal of Cultural Analytics (JOURNAL)
Journal identifiersISSN: 2371-4549 • E-ISSN: 2371-4549
PublisherCA: Journal of Cultural Analytics (PUBLISHER)
DOI10.22148/001c.116926
OpenAlexW4399120936
LanguageEN
Citations received4
References cited21

In this article we use an approach we term “speculative reading” to explore gaps in Sylvia Beach’s lending library records and the *Shakespeare and Company Project* datasets. We recast the problem of missing data as an opportunity and use a combination of time series forecasting, evolutionary models, and recommendation systems to estimate the extent of missing information and speculatively fill in some gaps. We conclude that the datasets include ninety-three percent of membership activity, ninety-six percent of members, and sixty-four percent to seventy-six percent of the books despite only including twenty-six percent of the borrowing activity. We then treat Ernest Hemingway as a test case for speculative reading: based on Hemingway’s known borrowing and all documented borrowing activity, we generate a list of books he might have borrowed during the years his borrowing is not documented; we then verify and interpret our list against the substantial scholarly record of the books he read and owned

Linguistics · Missing data · Computer Science · Human Mobility and Location-Based Analysis · Philosophy

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