A4 Refereed article in a conference publication
Probabilistic analysis of early modern British book prices
Authors: Tiihonen Iiro, Tolonen Mikko, Lahti Leo
Editors: Maud Ehrmann, Folgert Karsdorp, Melvin Wevers, Tara Lee Andrews, Manuel Burghardt, Mike Kestemont, Enrique Manjavacas, Michael Piotrowski, Joris van Zundert
Conference name: Conference on Computational Humanities Research
Publisher: CEUR-WS
Publication year: 2021
Journal: CEUR Workshop Proceedings
Book title : CHR 2021:Proceedings of the Conference on Computational Humanities Research 2021
Journal name in source: CEUR Workshop Proceedings
Series title: CEUR Workshop Proceedings
Volume: 2989
First page : 39
Last page: 48
ISSN: 1613-0073
Web address : http://ceur-ws.org/Vol-2989/short_paper9.pdf
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/67993093
Books are a valuable exception to the general rule that quantitative information about early modern history is scarce, as their survival rate during the period has varied between low and high tens of percents, and descriptive information summarizing their properties has been collected to library catalogues. However, one critical element that is essential for the numeric characterisation of a print product is most often missing - its price. In this paper, we use an exceptionally large data set of price information extracted from the English Short Title Catalogue (ESTC) for the early modern period to train a probabilistic model that predicts the price of a print product based on its physical properties. Our results suggest that just the simple physical properties of the print products can explain a significant proportion of the variation in prices. We use the model to quantitatively address the debated question about development of print product prices in eighteenth century Britain. We interpret the predictions of the model as a data driven narrative, and many of the developments it brings up can be readily linked with the relevant historical literature. © 2021 Copyright for this paper by its authors.
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