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Abstract

This work describes a computational method for reconstructing clusters of social relationships among early modern printers and publishers, the most determinant agents for the process of transformation of scientific knowledge. The method is applied to a dataset retrieved from the Sphaera corpus, a collection of 359 editions of textbooks used at European universities and produced between the years 1472 and 1650. The method makes use of standard bibliographic data and fingerprints; social relationships are defined as “awareness relationships”. The historical background is constituted of the production and economic practices of early modern printers and publishers in the academic book market. The work concludes with empirically validating historical case studies, their historical interpretation, and suggestions for further improvements by utilizing machine learning technologies.