2026 20.1
Critical Code Studies, Part II
Editors: Jeremy Douglass and Mark C. Marino
Front Matter
[en] Introduction: Reading Code in the Age of AIJeremy Douglass, University of California, Santa Barbara; Mark C. Marino, University
of Southern California
Abstract
[en]
This article introduces the second Digital Humanities Quarterly special issue on Critical Code Studies. It provides an overview of the contributions
to the issue while situating them within recent transformations in programming and
code reading brought about by generative AI and LLM-based coding assistants. Against
narratives that suggest automation diminishes the cultural significance of source
code, the essay argues that code remains a meaningful cultural text even when generated
or mediated by AI systems and that critical reading is therefore more urgent, not
less, in the age of coding assistants. Serving as a state-of-the-field report since
the first special issue, the article also surveys recent and forthcoming work in Critical
Code Studies, including Alan Blackwell’s Moral Codes, Daniel Temkin’s 44 Esolangs, Nick Montfort’s Narcissystem, Tom Boellstorff and Braxton Soderman’s Intellivision, and the forthcoming Inventing ELIZA by Sarah Ciston et al.
Articles
[en] Polysemicolon; Novice Programmers and Java KeywordsBriana Bettin, Michigan Technological University
Abstract
[en]
Most industrial programming languages leverage the English language for reserved keywords
– words which a program compiler recognizes as specific execution commands. The divide
between expert and novice programmers showcases an intriguing middle-ground by which
the polysemy of many keywords becomes revealed. This essay explores a sampling of
the multitude of keyword interpretations that a novice programmer may derive from
the Java language’s syntactic style and keywords specifically, and how the polysemy
of both “English” and “code” meanings to these terms affects the novice-expert programmer
transition.The transition from novice to expert, and the mapping of the career of
metaphor to these keywords as a part of that process, can have implications for both
teaching and learning programming.
[en] Rhetorical Strategies of Naming Practices in CodeKevin Brock, University of South Carolina
Abstract
[en]
The rhetorical significance of naming practices is widely understood, but it — and
many other rhetorical dimensions of language — are often overlooked in the domain
of software development, especially in regards to code languages and relevant practices
(as demonstrated in file names, functions, variables, and so on). While naming conventions
in code are typically recognized as inherently arbitrary, they are also tangled up
in numerous networks of community expectations, constraints, and mores, whether organizational
or interpersonally social in nature. Given Kenneth Burke's argument for the revealing
and concealing influences of terministic screens upon our engagement with the world
(by establishing ways of seeing and not seeing), naming conventions in code play an
important role in how meaningful invention occurs for human developers and readers
of code files. Despite the apparent triviality of such a component of software projects,
naming practices shine a light on the goals and values of a programmer in addition
to the functional intentions that they might have for the use of a given body of code.
[en] Counting Feeling: Affect Theory and Sentiment Analysis in TextBlobJeffrey Moro, University of Maryland
Abstract
[en]
Sentiment analysis encompasses a range of computational techniques for detecting and
quantifying the presence of affect and emotion in written texts. In this essay, I
use the techniques of critical code studies to offer a case study of one such sentiment
analysis tool called TextBlob, about which I advance two intertwined claims. First,
I map TextBlob’s reliance on a web of programmatic and textual dependencies, and how
in turn, TextBlob effaces these dependencies’ formal specificity in the service of
computational processing. This effacement supports my second claim: that TextBlob,
and sentiment analysis more generally, models affect as programmatically latent in
the smallest particles of language, which it then seeks to make available for computational
processing. I explore the consequences of this computational model of affect for digital
humanists seeking to integrate sentiment analysis and similar tools (including AI/LLMs)
into their work.
[en] The Epistemology of Code in the Age of Machine LearningEvan Buswell
Abstract
[en]
Code is an epistemic system predicated on the repression of state, but with the rise
of global optimization and machine learning algorithms, code functions just as much
to obscure knowledge as to reveal it. Code is constructed in response to two characteristics
of the twentieth century episteme. First, knowledge is represented as a process. Second,
this representation must be sufficient, such that its meaning is constituted by the
representational form itself. In attempting to meet these requirements, process is
separated into an essential part, code, and an inessential part, state. Although code
has a relationship with state, in order to construct code as an epistemic object,
state is limited and suppressed. This construction begins with the first formation
of code in the 1940s and reaches its modern form in the structured programming movement
of the later 1960s. But now, with the increasing dominance of global optimization
and machine learning algorithms in computing, it has become apparent that state is
vitally important, and yet our tools for understanding state are inadequate. This
epistemic inadequacy nevertheless serves those who would act dangerously and shun
responsibility for the consequences.
[en] Playing in the Gap: Analog Programming and the First Video Game ConsoleZachary Horton, University of Pittsburgh; Levi Burner, University of Maryland, College
Park
Abstract
[en]
In this essay we explore the relationship between code and the physical world through
an in-depth analysis of the analog video game Volleyball, one of the first games for
the first video game console ever produced, the Magnavox Odyssey, in 1972. We address
the relative lack of critical humanities scholarship on analog programming by exploring
the many ways that this code differs from digital program code, and the implications
of the relations it establishes between user, digital logic, and the surrounding environment.
We represent this program in four levels of abstraction: as hardware (circuitry),
as mathematical models, as block program notation (historical analog programming notation)
revealing the program’s logic flow, and as game, when combined with player input and
human language instructions. We conclude that Volleyball is an example of code that
enrolls its end users as fundamental constituents in its primary program loop, and
thereby “plays in the gap” between the symbolic and the real, the analog and the digital,
the inside and outside of code. We explore this model as multi-level code, arguing
that it suggests new perspectives and modes of analysis for digital code as well.
[en] Reading Note G: Ada Lovelace and the Clerical Labor
of CodeworkZachary Mann, University of Southern California
Abstract
[en]
This article examines human-machine co-authorship as it represented by Ada Lovelace
in her famous translation of and appendices to L. F. Menabrea’s “Sketch of The Analytical
Engine Invented by Charles Babbage.” Lovelace's
translation notes and correspondence with Charles Babbage are read alongside the
Engine itself, as a platform, and the histories of calculating engines, software
development, and nineteenth-century clerical labor. Inspired by critical code
studies, the article performs a close reading of what is today referred to as the
“first computer program,” a sequence of steps that Lovelace
adds to her translation’s final “Note G” as an example of
something the Engine can do. Ultimately, the article argues that the gendered power
structures of collaborative work in Lovelace’s time — and the challenges women
authors faced in the nineteenth century more broadly — influenced understandings of
machine programming, and that Lovelace’s representation of the human-machine
relationship in the first programmable calculating machine complicates the
organizational structures of both clerical labor and software design.
[en] Defactoring Pace of ChangeMatt Burton, University of Pittsburgh; Joris van Zundert, Huygens Institute of the
Royal Netherlands Academy of Arts and Sciences
Abstract
[en]
Code, the symbolic representation of computer instructions driving software, has long
been a part of research methods in literary scholarship. However, the bespoke code
of
data and computationally inflected Digital Humanities research is not always a part
of the final publication. We emphasize the need to elevate code from its generally
invisible status in scholarly publications and make it a visible research output.
We
highlight the lack of conventions and practices for theorizing, critiquing, and peer
reviewing bespoke code in the humanities, as well as the insufficient support the
dissemination and preservation of code in scholarly publishing. We introduce “defactoring”
as a method for analyzing and reading code used
in humanities research and present a case study of applying this technique to a
publication from literary studies. We explore the implications of code as methodology
made material, advocating for a more integrated and computationally informed mode
of
interacting with scholarship. We conclude by posing questions about the potential
benefits and challenges of linking code and theoretical exposition to foster a more
robust scholarly dialogue.
[en] Reading Code AloudMace Ojala, Ruhr University Bochum
Abstract
[en]
In this article, I present reading computer source code aloud, and reflect on it together
in dialogue, as a method which offers new forms of engagement with code and programming.
With my peer discussion partner, we experimented with this methodology by exchanging
recorded audio messages in a research project involving computational data-analysis.
We discovered that abandoning the screen allowed us to de-explain, de-familiarize
and de-contextualize code we had programmed, and negotiate new, shared insight of
it as a cultural and situated object through re-explanation, re-familiarization, and
re-contextualization of our experience of code.
Articles
[en] Do all politicians sound the same? Comparing model explanations to human responsesOtto Tarkka, TurkuNLP, University of Turku; Kimmo Elo, University of Eastern Finland
& Centre for Parliamentary Studies, University of Turku; Filip Ginter, TurkuNLP, University
of Turku; Veronika Laippala, TurkuNLP, University of Turku
Abstract
[en]
It is sometimes said that all politicians sound the same with their speeches mired
in political jargon full of clichés and false promises. To investigate how distinct
the plenary speeches of political parties truly are and what linguistic features make
them distinct, we trained a BERT classifier to predict the party affiliation of Finnish
members of parliament from their plenary speeches. We contrasted and compared model
performance to human responses to see how humans and the model differ in their ability
to distinguish between the parties. We used the model explainability method SHAP to
identify the linguistic cues that the model most relies on. We show that a deep learning
model can distinguish between parties much more accurately than the respondents to
the questionnaire. The SHAP explanations and questionnaire responses reveal that whereas
humans tend to rely on mostly topical cues, the model has learned to recognize other
cues as well, such as personal style and rhetoric.
[en] Facets of Friction: Investigating
epistemological friction between computing and the humanities to support Digital
Humanities computing educationAnna Sollazzo, University of Glasgow
Abstract
[en]
Learning computing can often be challenging to Digital Humanities (DH) students
because its knowledge-production practices and values do not necessarily align
with those of humanistic inquiry. Further, the breadth of the technologies used
in the field can make it difficult to identify which computational ideas and
skills are most essential to teach in DH. This paper argues that, in order to
teach students to enact a paradigm of 'humanistic computing' which is reflective
of humanistic interests and ways of knowing, it is necessary to centre the
epistemological friction that exists between computing and the humanities. It
proposes a four-faceted framework to aid in the identification and exploration
of that friction, with the intention that it be used by DH educators to
structure their computing curriculum – regardless of the technologies or level
of abstraction it engages with – and by students or even practitioners to
scaffold a critical approach to computational DH work.
[en] Losing the API: Developing Novel Methods for Scraping Black TwitterAndrew Lowe Mohammed, The University of Maryland, College Park; Alisa Hardy, The University
of Maryland, College Park; Rianna Walcott, The University of Maryland, College Park;
Tynesha McCullers, North Carolina State University; Abigail Vazquez Rosario, The University
of Maryland, College Park
Abstract
[en]
As digital platforms continually evolve, rapid changes to platform affordances quickly
render digital tools and data collection methods obsolete. Researchers of digital
culture therefore must proactively adapt to the ephemerality of data. This paper examines
these challenges within the context of Twitter (X) following its 2022 acquisition
by Elon Musk, and the subsequent limiting of access to the API for data collection.
Using a combination of manual data-collection practices and Zeeschuimer , a browser
extension that collects social media data while browsing, researchers developed a
novel data collection method, and model methodological adaptability within shifting
digital terrains.
[en] Open Tool Registries! Resolving the Directory
Paradox with Wikidata Till Grallert, Humboldt-Universität zu Berlin; Sophie Eckenstaler, Deutsches Dokumentationszentrum
für Kunstgeschichte – Bildarchiv Foto Marburg; Claus-Michael Schlesinger; Nicole Dresselhaus,
Humboldt-Universität zu Berlin; Isabell Trilling, Humboldt-Universität zu Berlin;
Sophie Stark, Humboldt Universität zu Berlin
Abstract
[en]
This paper introduces the conceptual framework for open and community-curated
tool registries, posing that such registries provide fundamental value to any
field of research by acting as curated knowledge bases about a community’s past
and current methodological practices as well as authority files for individual
tools. The modular framework of a basic data model, SPARQL queries, bash
scripts, and a prototypical web interface builds upon the well-established and
open infrastructures of Wikimedia, GitLab, and Zenodo for creating, maintaining,
sharing, curating, and archiving linked open data. We demonstrate the
feasibility of this framework by introducing our concrete implementation of a
tool registry for digital humanities, initially repurposing data from existing
silos, such as TAPoR and the SSH Open Marketplace, and retaining the established
TaDiRAH classification scheme while being open to communal editing in every
aspect.
[en] From the Rock Wall to Wikipedia: Sites of
Digital Connection and Repair in the Community-Engaged ClassroomCourtney Rivard, UNC-Chapel Hill; Alexandra Odom, UNC-Chapel Hill; Carly Schnitzler,
Johns Hopkins University; Katherine Stein, UNC-Chapel Hill; Rolando Rodriguez, UNC-Chapel
Hill; Kathryn Wall, The Marian Cheek Jackson Center for Saving and Making History;
Anna Spencer, The Marian Cheek Jackson Center for Saving and Making History; Kyle
Cunningham, UNC-Chapel Hill; Sage Clausen, UNC-Chapel Hill; Sarah Davey, UNC-Chapel
Hill
Abstract
[en]
In the Spring of 2023, we collaborated on the development of a project for ENGL
114: The Rhetorics of Data, that tasked students with exploring the relationship
between knowledge production and data through a collaborative Wikipedia project
with the Marian Cheek Jackson Center for Saving and Making History, a nonprofit
organization that preserves and celebrates the history of Chapel Hill and
Carrboro's Black communities. To amplify the Jackson Center's ongoing oral
history work digitally, the organization’s public history leaders came together
with a team at UNC-Chapel Hill to create a public digital humanities project for
undergraduates that would offer students the opportunity to gain needed digital
and data literacy skills by meaningfully contributing to the local community. In
this case study, we outline: (1) the formation of this collaborative, reciprocal
partnership that aids in the mission of the Jackson Center, (2) the power and
intrinsic inequities in Wikipedia, and (3) the critical data literacies students
develop through such a public humanities project. Ultimately, we argue that
Wikipedia can serve as a bridge between community partners and classrooms of
higher-ed institutions by centering community histories in accordance with the
mission of community organizations to achieve key pedagogical goals, including
the development of critical data literacy skills.
[en] Stylometric Consistency Patterns in Translation
of Spoken Chinese to Written English: A Corpus Analysis of the CoVoST
DatasetVincent Chieh-Ying Chang, Tamkang University
Abstract
[en]
This study examines stylometric consistency patterns in professional human
translations of spoken Chinese to written English, using the CoVoST corpus.
Moving beyond traditional translation quality assessment, the investigation
studies how human translators navigate the speech-to-text modality shift and
whether this process produces domain-invariant stylistic regularities. Through a
framework combining stylometric analysis, machine learning, and digital
humanities critique, I identify a “consistency bias” —
manifested as standardized lexical diversity, flattened syntactic structures,
and repetitive discourse patterns — that reveals how professional constraints
and cognitive processing shape translation output. My analysis of 16,899
human-translated English sentences, with detailed statistical comparison of 300
sentences against contemporary spoken English baselines, demonstrates that
speech-to-text translation exhibits significantly reduced lexical diversity
(Cohen's d=0.34, p<0.001),
shallower syntactic structures (d=0.33, p<0.001), and narrower modal verb usage (d=0.43,
p<0.001) compared to original spoken
English. These findings illuminate the cognitive and professional constraints
shaping human translation practice; future research might consider how such
patterns subsequently inform machine translation systems trained on
human-translated corpora.
[en] Multilingualism as Infrastructural Imperative:
Language Diversity in Digital Knowledge Commons [es] El multilingüismo como imperativo en la infraestructura digital: Diversidad lingüística
en los bienes comunes de conocimiento[pt] Multilinguismo como Imperativo Infraestrutural: Diversidade Linguística em Bens Comuns
Digitais de ConhecimentoAlan Colin-Arce, University of Victoria; Graham Jensen, University of Victoria; Brittany
Amell, University of Victoria; Ray Siemens, University of Victoria
Abstract
[en][es][pt]
Multilingualism has been gaining importance in the digital humanities and
scholarly communication, but the infrastructure used to disseminate
scholarship has mostly remained in English. Monolingual research
infrastructure creates a language barrier for non-Anglophone
speakers to access scholarly outputs and reinforces the idea that
English is the only legitimate language for disseminating scholarship.
Drawing from the debates on multilingual DH and scholarly publishing, we
argue that any digital research infrastructure purporting to support
knowledge diversity across disciplinary and national contexts must
actively work to provide tools to facilitate, publish, and promote
research in languages other than English. To show how multilingualism
can guide infrastructure development and foster connections with diverse
audiences, we describe the translation process of the interface of a
research infrastructure, the Humanities and Social Sciences Commons,
into four languages: French, Spanish, Bangla, and Portuguese.
El multilingüismo ha ido ganando importancia en las humanidades digitales
y la comunicación académica, pero la infraestructura utilizada para
difundir resultados de investigación se ha mantenido principalmente en
inglés. La infraestructura de investigación monolingüe es una barrera
que limita el acceso a la información académica para las personas no
anglófonas y refuerza la idea de que el inglés es el único idioma
legítimo para difundir conocimiento. Con base en los debates recientes
en las humanidades digitales multilingües y la publicación académica,
argumentamos que cualquier infraestructura de investigación digital que
busque fomentar la diversidad de conocimientos en distintos contextos
disciplinares y nacionales debe trabajar activamente para proporcionar
herramientas que faciliten y promuevan la investigación y la publicación
en idiomas distintos del inglés. Para mostrar cómo el multilingüismo
puede guiar el desarrollo de infraestructuras y fomentar conexiones con
audiencias diversas, en este artículo describimos el proceso de
traducción de la interfaz de una infraestructura de investigación, el
Humanities and Social Sciences Commons, a cuatro idiomas: francés,
español, bengalí y portugués.
O multilinguismo tem ganhado importância nas humanidades digitais e na
comunicação acadêmica, mas a infraestrutura utilizada para divulgar o
conhecimento científico mantém-se principalmente em inglês. Uma
infraestrutura de pesquisa monolíngue cria uma barreira linguística para
falantes não-anglófonos acessarem produções acadêmicas e reforça a ideia
de que o inglês é a única língua legítima para difundir o conhecimento
científico. Com base nos debates sobre humanidades digitais multilíngues
e publicações acadêmicas, argumentamos que qualquer infraestrutura
digital de pesquisa que pretenda apoiar a diversidade de conhecimentos
em contextos disciplinares e nacionais deve trabalhar ativamente para
fornecer ferramentas que facilitem, publiquem e promovam pesquisa em
línguas diferentes do inglês. Para mostrar como o multilinguismo pode
orientar o desenvolvimento da infraestrutura e fomentar conexões com
públicos diversificados, descrevemos o processo de tradução da interface
de uma infraestrutura de pesquisa, o Humanities and Social Sciences
Commons, para quatro idiomas: francês, espanhol, bengali e
português.
[en] Striving towards automated writing – Views on
authorship in story generation research Tuuli Hongisto, University of Helsinki
Abstract
[en]
This article examines how authorship is approached in story generation research
publications. Story generation research forms its own, distinctive context in
which computer-generated literary texts are being produced. Through text
analysis and comparisons to other forms of computer-generated literature, the
article examines what kind of rhetoric is used when the authorship of
computer-generated texts is described in this context, and how the roles of the
programmers and the program are characterised. The findings suggest that the
approach to authorship in story generation research is mainly technical,
referring strictly to the production process of the text, and leaving out the
meaning of authorship as responsibility and accountability of the work as an
aesthetic whole. This technical view affects how human-computer relations are
discussed in the research, as “human-generated” and
“computer-generated” texts are contrasted with each
other. Furthermore, this dichotomy of the human and the machine affects how the
produced stories are evaluated.
[en] Reconfiguring the Ideal Order: Ablation and
Field Formation in the Twentieth-Century Nigerian Novel in EnglishGrant Hamilton, Chinese University of Hong Kong; Eli Park Sorensen, Chinese University
of Hong Kong
Abstract
[en]
Computational literary studies has developed sophisticated methods for detecting
textual relationships – similarity networks, text reuse detection, semantic
comparison – yet these approaches remain largely constrained to pairwise
analysis. They reveal which texts resemble one another but cannot capture how
individual works contribute to the collective semantic architecture of a corpus.
This paper introduces a methodology that addresses this gap by shifting focus
from text-to-text relationships to field formation. Treating a corpus as an
integrated semantic space constructed through GloVe word embeddings, the method
employs ablation testing – the systematic removal of individual texts followed
by retraining – to measure each text’s structural contribution to that space.
Procrustes analysis quantifies the geometric difference between full and ablated
embeddings, and an iterative protocol with consistency-based exponential decay
filtering distinguishes genuine semantic disruption from algorithmic noise. The
resulting “disruption scores” identify texts that are
structurally necessary to a corpus’s semantic field, capturing a dimension of
textual significance irreducible to similarity, centrality, or explicit
citation. Drawing on T.S. Eliot’s concept of the “ideal
order” as a heuristic for the relational and achronological
dynamics the model quantifies, the paper demonstrates the methodology on a
corpus of 142 twentieth-century Nigerian novels in English. Results validate the
approach against established literary-historical scholarship while also
surfacing critically overlooked texts whose structural significance warrants
further attention. The methodology is portable across corpora and offers
scholars a data-driven means of engaging intertextuality’s foundational insight:
that literary significance is relational, systemic, and collectively
constituted.
[en] Infrastructures of Listening: The ManoWhisper
Podcast Analysis PipelineNick Ruest, York University, Digital Scholarship Infrastructure; Brianna I. Wiens,
University of Waterloo, English Language & Literature; Karmvir K. Padda, University
of Waterloo, Sociology and Legal Studies; Shana MacDonald, University of Waterloo,
Communication Arts
Abstract
[en]
Podcasting has become a central infrastructure for the circulation and
normalization of misogynistic and extremist ideologies, yet the scale, length,
and affective density of audio content pose significant challenges for critical
qualitative research. This paper introduces ManoWhisper, a feminist
computational research infrastructure designed to support the large-scale
analysis of misogynistic podcast ecosystems while preserving the contextual
depth required for interpretive and ethical engagement. ManoWhisper combines
automated audio acquisition, transcription, sentence-level classification,
indexing, and visualization within a searchable web-based interface that enables
researchers to move between computational pattern detection and close
qualitative reading. Grounded in a feminist methodology of dwelling, the tool is
designed to slow analysis, foreground emotional labour, and support
collaborative research across varying levels of technical expertise. It allows
for an in-depth consideration of more extremist media ecosystems across a
variety of key factors. This paper documents ManoWhisper’s end-to-end pipeline,
from content collection and transcription to classification, indexing, and
interface design. Further we demonstrate its application across multiple
peer-reviewed and public-facing research projects examining misogyny,
masculinity, and gender-based extremism in podcasting, as well as how it is
being used in policy and government institutions. We position ManoWhisper as
methodological infrastructure that redistributes analytic capacity, makes
repetition and scale visible, and enables ethically grounded engagement with
harmful media. We conclude by reflecting on the tool’s limitations, its
implications for feminist digital methods, and its relevance for understanding
how misogynistic content circulates not only across media platforms but into
emerging domains such as AI training data.
[en] The Eras Tour: Machine Learning for Dating
Historical Texts from Greco-Roman EgyptDanushka Bandara, Fairfield University; Adrian Gallant, Fairfield University; Habibul
Huq, Fairfield University; Fatima Chowdhury, Fairfield University; Jack Stow, Fairfield
University; Giovanni Ruffini, Fairfield University
Abstract
[en]
Accurate dating of historical texts is essential for understanding cultural and
historical narratives. However, traditional methods, such as paleographic and
physical examination, can be subjective, costly, and potentially damaging to
manuscripts. This paper introduces a machine learning approach to predicting the
authorship dates of historical texts by using named entities — specifically,
person and place names — as temporal markers. Using a dataset from Trismegistos,
which includes metadata on the earliest and latest possible writing dates, we
apply regression models to estimate text origins. While linear models like Lasso
and Ridge Regression showed limited success, nonlinear models, including Random
Forest, XGBoost, and Neural Networks, performed significantly better, with
ensemble methods delivering the best results. The top-performing ensemble model
achieved a mean absolute error of 45.7 years, surpassing traditional techniques.
This study demonstrates the potential of named entities as temporal indicators and
the effectiveness of ensemble learning in capturing complex historical patterns, offering
a scalable, non-destructive alternative to traditional methods.
[en] The Application of Latent Semantic Analysis to
the Voynich ManuscriptColin Layfield, University of Malta; Lisa Fagin Davis, Medieval Academy of America
Abstract
[en]
The Voynich Manuscript (VM) is a medieval manuscript likely written in the 15th
century (Yale Univ., Beinecke Rare Book & Manuscript Library MS 408).
https://beinecke.library.yale.edu/collections/highlights/voynich-manuscript
The manuscript is written in an unknown language or code using an
unidentified set of symbols that has yet to be made legible. Additionally, the
codex contains many strange and fantastical images of plants, people, and
cosmological/zodiac illustrations, the meaning of which are also unknown. One of
the main research avenues into the VM is to examine its textual content to
understand how it behaves relative to known texts; this can provide insight as
to whether the mysterious writings contain decipherable text or not. In this
paper, we explore the coherence and flow of the manuscript using Latent Semantic
Analysis (LSA). LSA is a technique that may help ascertain whether the behavior
of the text within the VM shows evidence of a coherent flow of topical content,
by comparative analysis of text samples that are near each other, farther away
from each other, at section breaks, or even page breaks. The advantage of this
strategy is that LSA analysis can be undertaken without actually knowing the
meaning of the text. We expect portions of text that are near to each other to
have a relatively high similarity score, that is, to be potentially semantically
related. We also expect that at anticipated topic breaks (pages or sections),
the similarity score between adjacent text blocks would be smaller, as the
breaks seem to represent a change in topic. Both of these patterns are observed
in the control manuscript studied as proof-of-concept experiments. Patterns then
observed in several sections of the VM suggest that there may be an overall
coherence to the text.
Case Studies
[en] Decoding and Encoding Welsh Manuscript Culture: Scribes, Scripts and TEIHuw Jones, Cambridge University Library; Yasmin Faghihi, Cambridge University Library;
David Parsons, University of Wales; Jason Evans, The National Library of Wales; Gruffudd
Antur, the University of Wales
Abstract
[en]
Daniel Huws’s Repertory of Welsh Manuscripts and Scribes c.800–c.1800 was published in 2022 to widespread acclaim – a “giant of scholarship” which “...
handed the world the keys to unlock the great riches of a thousand years of Welsh
manuscript culture” . Containing descriptions of c.3,300 manuscripts from sixty-eight
repositories, along with detailed indexes and plates illustrating scribal hands, the
Repertory is “... the kind of work upon which all others build” . In his introduction
to the Repertory, Huws immediately points to the future, writing that it “... belongs
to that class of publication which can only reach maturity in a second edition” .
This case study describes work towards the production of that edition, not as an expanded
or revised set of printed volumes but as a dataset. First, we set the Repertory in
the context of catalogues of Welsh manuscripts, and in the wider context of digital
resources derived from manuscript descriptions. Then we describe the process of converting
the Repertory into a dataset, and how this process, while technical in nature, served
as a close reading of its scope and purpose. We offer some practical guidance on the
conversion of print volumes to datasets and outline some initial research findings.
Finally, we suggest some possible next steps for the Repertory, covering issues such
as access and sustainability, integration with other resources and minimal computing
approaches to analysing and surfacing the data.
Reviews
[en] A Review of Manuale di
letteratura elettronicaGiuseppe Arena, University of Catania
Abstract
[en]
This review analyzes Fabrizio Venerandi’s Manuale di
letteratura elettronica (2024), a work that aims to introduce a
non-specialist audience to the world of born-digital literature, with a
particular focus on text adventures and narrative video games. The volume
highlights the centrality of video games as “new literature”
and their ability to redefine the traditional categories of author, reader and
text, combining a historical perspective with an eminently practical and
educational approach. Through an extensive mapping of works and tools, the
manual emphasizes its value as a catalogue
raisonné and as an invitation to recognize video games as one of
the main contemporary laboratories of electronic literature, raising questions
of preservation, authorship, and critical use of digital medium that are central
to the Digital Humanities as well.
