Abstract
This essay uses network metrics (centrality, density, clustering coefficients) to account for shifts in dedicatory practice resulting from political crises, religious turmoil, and changes in book production practices. It constructs a network from the names that appear in dedications of EEBO-TCP texts; names are detected using the linguistic markup from the EarlyPrint project. The essay argues that we learn more about early modern book history by constructing networks of all the names that appear in dedications, not just those of authors, printers, and patrons. The network includes a mixture of religious and political figures, literary personalities, fictional characters, and bookmaking professionals, because this is the full range of names that dedicatory practice covers in the period. By proceeding in this way, network metrics can account for a range of dedicatory phenomena, including Queen Elizabeth’s popularity on both sides of the political aisle long after her death and, especially, consolidation around non-contemporary names in dedicatory practice as a result of both the Civil War and the Restoration. The imaginative networks revealed by early modern dedications are organized mainly around untimely figures from the recent and distant past, but despite this the networks are sensitive to historical change, especially at moments of political and social crisis.
Highlights
In A Description of the Famous Kingdome of Macaria (1641), Samuel Hartlib begins his book with a dedication to the “High and Honorable Court of Parlia ment,” but in the text of the dedication he saw fit to name a few people who have little do with the Parliament of the early 1640s: TO THE HIGH AND HONORABLE COURT OF PARLIAMENT
WHereas I am confident, that this Honorable Court will lay the Cor ner Stone of the worlds happinesse before the final recesse thereof, I have adventured to cast in my widowes mite into the Tresurie, not as an Instructer, or Counsellour, to this Honourable Assembly, but have delivered my conceptions in a Fiction, as a more man nerly way, having for my pattern Sir Thomas Moore, and Sir Fran
Hartlib names two other individuals, More and Bacon, in the body of the dedication, and he even labels them as his “pattern” or role models in this publishing venture
Summary
The data for this project comes from EarlyPrint, the digital project on which I’m currently a collaborator. I collected data from the text sections marked up as dedications in the 52,418 EarlyPrint texts 1 you can see the same names from Hartlib’s Macaria that I showed in the quote above, with the wordlevel markup that EarlyPrint added to EEBOTCP texts. This markup provides lemma, part of speech, and regularized spellings for every word in a text. The linguistic markup was provided by MorphAdorner, a Java NLP library developed by Philip Burns and Martin Mueller for historical texts, with extensive training data and specialized code for early modern English.[20] MorphAdorner’s part of speech tagging allowed me to collect proper nouns more accurately.
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