• Konrad Nicinski

Institute of Literary Research, Polish Academy of Sciences

Nowa Panorama Literatury Polskiej (New Panorama of Polish Literature, NPLP.PL) is a platform for presenting research results in the digital environment; it is a part of the Digital Humanities Centre at the Institute of Literary Research. The interdisciplinary team of the New Panorama of Polish Literature is currently working on the second Polish issue of TEI technical standard and the first that is adjusted to the edition of nineteenth- and twentieth- century collections of literature, including non-fictional forms, such as letters and diaries. The first scholarly digital edition in this series consists of twentieth-century letters of poets related to the leading Polish émigré magazine (Wiadomości), Jan Lechoń and Kazimierz Wierzyński, and the magazine’s editor, Mieczysław Grydzewski.

This paper will present some problems encountered during work on the edition, primarily concerning the issues connected with annotations/notes in traditional editions and their adaptation into the scholarly digital edition. One of our project’s principles is that the traditional and digital scholarly editions should be parallel. We are convinced that they may have different uses and offer different features and possibilities. So the objective of this paper is to show how the solutions suitable for traditional scholarly editions work in the digital environment. The particular problem is how to adjust the annotations to the rules of scholarly digital edition, above all to TEI technical standard. The aim of the presentation will be to search for answers to the following questions:

-  how to use possibilities given by TEI elements and attributes?

-  can the description of TEI elements replace the foot- or endnotes?

-  why (in our project) do traditional footnotes after implementation into the digital edition demand further reworking, sometimes both editorial and factual?

• Leah Henrickson

Loughborough University

Natural language generation (NLG) – the process wherein computers translate data into readable human languages – has become increasingly present in our modern digital climate. In the last decade, numerous companies specialising in the mass-production of computer-generated news articles have emerged; National Novel Generation Month (NaNoGenMo) has become a popular annual event; #botALLY is used to identify those in support of automated agents producing tweets. Yet NLG has not been subject to any systematic study within the humanities.

This paper offers a glimpse into the social and literary implications of computer-generated texts and NLG. More particularly, this paper examines how NLG output challenges traditional understandings of authorship and what it means to be a reader. Any act of reading engages interpretive faculties; modern readers tend to assume that a text is an effort to communicate a particular pre-determined message. With this assumption, readers assign authorial intention, and hence develop a perceived contract between the author and the reader. NLG, however, brings this contract into question. The author of a computer-generated text is often an obscured figure, an uncertain entanglement of human and computer. How does this obscuration of authorship change how text is received? What does this obscuration say about our new digital humanity?

This paper will present the results of a series of studies conducted by the researcher to discern how readers attribute authorship to computer-generated texts. These results suggest that many everyday readers regard NLG as more than just tools for manifesting human vision. Indeed, systems are attributed agency in and of themselves. Consideration of such implications of NLG is vital as we venture deeper into the digital age. Computer-generated texts may not just challenge traditional understandings of authorship: they may engender new understandings of authorship altogether as readers explore the conceptual gap between human and computer language production.

• Roel Smeets

Radboud University Nijmegen

Traditionally, the critique of literary representation hinges on ‘symptomatic’ forms of reading in which textual elements are regarded as expressive of deeper lying ideological issues (Jameson 1981, Althusser & Balibar 1997). In the Digital Humanities, a textual approach is operationalised which mainly targets measurable elements on the textual surface (Best & Marcus 2009). For a digitally oriented critique of representation, this creates a tension between the text’s surface and it’s ‘hidden’ depths that reside between the lines. Digital methods for literary studies are evidently useful for describing, categorizing and measuring surface elements of the text, but the study of literary representation mostly focuses on that what is not directly visible or apparent. How could digital methods contribute to the analysis of ideological constructs that lie dormant in the margins of the text?

In this talk, the merits and pitfalls of a Digital Humanities critique of representation are considered by focusing on character representation in contemporary Dutch literature, as representational hierarchies between characters have been a fruitful point of departure for symptomatic critiques of representation (e.g. Pattynama 1994, Meijer 1996, Pattynama 1998, Minnaard 2010). The focus lies on a sample corpus of 170 recent Dutch novels containing ± 2100 characters, of which extensive demographic information (gender, age, place of birth, place of residency, level of education, profession) has been gathered  (Van der Deijl, Pieterse, Prinse, Smeets 2016), as well as thematic roles (family, lover, colleague, friend, enemy) between all characters. Through a network analytical approach, every character in the corpus is ranked according to statistical centrality measures in order to provide a quantitative view on the centrality of certain character demographics.

The resulting character rankings will be used to explore the character representation of gender, ethnicity and class in the corpus. To what extent do such empirically informed, data-driven patterns on the textual surface reveal something of the deeper lying ideological issues in the text? It is argued that symptomatic and surface reading are not mutually exclusive, but can potentially enhance one another, provided that one stays away from problem solving rhetorics (Cecire 2011) and neopositivist assumptions (Ramsay 2011, Tom Eyers 2017).