Conference Agenda

In 2019, John Bryant, Wyn Kelley, and I released a beta-version of a digital edition of Herman Melville's last work _Billy Budd, Sailor_. This TEI-encoded edition required nearly 10 years of work to complete, mostly owing to the fact that this last, unfinished work by Melville survives in an incredibly complicated manuscript that demonstrates about 8 stages of revision. The digital edition (https://melville.electroniclibrary.org/versions-of-billy-budd) has since been updated, and it presents a fluid-text edition (Bryant 2002) in three versions: a diplomatic transcription of the manuscript, a 'base' (or clean readable) version of the manuscript, and a critical, annotated reading text generated from the base version. Nevertheless, it remained questionable to me how we could effectively use all of the sophisticated descriptive markup of the manuscript transcription for critical purposes. What is missing, in other words, is an effective analysis of the genesis of this work.

In this talk I would like to demonstrate recent work on text analyses on the TEI XML data of the manuscript for a chapter-in-progress of my book-length project entitled _Melville’s Codes: Literature and Computation Across Complex Worlds_ (co-authored with Dennis Mischke, and under contract with Bloomsbury). First I generated and visualised basic statistics of textual phenomena (additions, deletions, and substitutions, e.g.) using XPath expressions combined with the R programming language. I then used the XML2 and TidyText libraries in R to perform more sophisticated analyses of the manuscript in comparison to Melville's oeuvre. Ultimately the analyses show that _Billy Budd_ ought to be read as a testament to incompleteness and negation.

In general, Melville’s use of negations and negative sentiments increased throughout his fictional work. Although this trend drops off in the late poetry, _Billy Budd_ has the highest number of negations in all of Melville’s oeuvre. It also has more acts of deletion than addition in the manuscript. Yet these trends need to be analysed in the context of Melville’s incomplete manuscript, the ‘ragged edges’ of which demonstrate not only a late tendency to increase negative words and ideas, but also, in late revisions, to complicate the main characters of the novel (particularly Captain Vere) who represent justice in the story. Like 'Benito Cereno', the codes of judgment are shown to be inadequate to the task of reckoning with the tragic conditions represented in Melville’s final sea narrative. This inadequacy is illustrated by Vere’s reaction to Billy’s death, which is framed as a computation, an either/or conditional: ‘Captain Vere, either thro stoic self-control or a sort of momentary paralysis induced by emotional shock, stood erectly rigid as a musket in the ship-armorer's rack’ (Chapter 25). This thematic incompleteness is not only a metaphor in the text but a metaphor of the text of this incomplete story.

Christopher Ohge is Senior Lecturer in Digital Approaches to Literature at the School of Advanced Study, University of London. His book _Publishing Scholarly Editions: Archives, Computing, and Experience_ was published in 2021 by Cambridge University Press. He also serves as the Associate Director of the Herman Melville Electronic Library.

Sentiment analysis (SA), one of the most active research areas in NLP for over two decades, focuses on the automatic detection of sentiments, emotions and opinions found in textual data (Liu, 2012). Recently, SA has also gained popularity in the field of Digital Humanities (Schmidt Burghardt & Dennerlein, 2021). This contribution will present the analysis of a TEI encoded digital scholarly edition of Spanish periodicals using a machine learning approach for sentiment analysis as well as the re-implementation of the results into TEI for further retrieval and visualization.