Faculty Seminar On Collaboration Syllabus

This is a collectively-built, in-progress syllabus for a faculty seminar on the topic of collaboration at Swarthmore College, Spring 2016. Topics include competing definitions of collaboration across disciplines, formal and informal collaboration, rich descriptions of collaboration, metrics and measures of collaborations, digital and analog tools for collaboration, literary and historical forms of collaboration, cost/benefit analyses of collaboration, crossinstitutional collaborations, institutional versus individual collaborations, collaboration narratives, failed or tragic collaborations, and teaching collaborations. Seminar members include statisticians, historians, psychologists, visual artists, literary critics, physicists, philosophers, engineers, education studies researchers, linguists, art historians, and computer scientists. Our format will accommodate both discussions of readings based on the syllabus as well as small experiments, and planning for possible future related projects

When Computer Science Met Austen and Edgeworth

Jesse Rosenthal states in the introduction to the 2017 special issue of Genre : ‘data is a big deal right now. We cannot talk about data and the novel without recognizing the particular importance that the question of data has in literary studies’ (2017, p. 4). This paper is positioned at the intersection of Literary Studies and Computer Science. It explores the appli cation of computer based analysis to novels from the long eighteenth century (an historical period between approximately 1640 to 1830) and, specifically, examines the insights that are gained by using these tools to compare novels by Jane Austen and Maria Edgeworth. It also considers the challenges these methods may present for Humanities scholars, and the benefits of combining computational approaches with close reading. The title of this paper comes from the film ‘When Harry Met Sally...’ (1989). The li ne at the heart of the film proposes that ‘men and women can’t be friends because the sex part always gets in the way’, before ultimately demonstrating that, for Harry and Sally, combining sex with friendship leads to a positive relationship. This analogy echoes some of the arguments against the use of digital analysis in literary studies, or, to rephrase it ‘literary studies and computer science can’t be friends because the tech part always gets in the way’, but it also suggests a possible way forward

When Computer Science Met Austen and Edgeworth

Jesse Rosenthal states in the introduction to the 2017 special issue of Genre : ‘data is a big deal right now. We cannot talk about data and the novel without recognizing the particular importance that the question of data has in literary studies’ (2017, p. 4). This paper is positioned at the intersection of Literary Studies and Computer Science. It explores the appli cation of computer based analysis to novels from the long eighteenth century (an historical period between approximately 1640 to 1830) and, specifically, examines the insights that are gained by using these tools to compare novels by Jane Austen and Maria Edgeworth. It also considers the challenges these methods may present for Humanities scholars, and the benefits of combining computational approaches with close reading. The title of this paper comes from the film ‘When Harry Met Sally...’ (1989). The li ne at the heart of the film proposes that ‘men and women can’t be friends because the sex part always gets in the way’, before ultimately demonstrating that, for Harry and Sally, combining sex with friendship leads to a positive relationship. This analogy echoes some of the arguments against the use of digital analysis in literary studies, or, to rephrase it ‘literary studies and computer science can’t be friends because the tech part always gets in the way’, but it also suggests a possible way forward

Affordances and limitations of algorithmic criticism

Humanities scholars currently have access to unprecedented quantities of machine-readable texts, and, at the same time, the tools and the methods with which we can analyse and visualise these texts are becoming more and more sophisticated. As has been shown in numerous studies, many of the new technical possibilities that emerge from fields such as text mining and natural language processing can have useful applications within literary research. Computational methods can help literary scholars to discover interesting trends and correlations within massive text collections, and they can enable a thoroughly systematic examination of the stylistic properties of literary works. While such computer-assisted forms of reading have proven invaluable for research in the field of literary history, relatively few studies have applied these technologies to expand or to transform the ways in which we can interpret literary texts. Based on a comparative analysis of digital scholarship and traditional scholarship, this thesis critically examines the possibilities and the limitations of a computer-based literary criticism. It argues that quantitative analyses of data about literary techniques can often reveal surprising qualities of works of literature, which can, in turn, lead to new interpretative readings

The Circuits of Reading the Digital: Some Models

In theorizing the digital text, I will take a two-pronged approach: a) what aspects of reading cannot be accounted for by the types of digital textual analysis done so far in the digital humanities, and b) how can technology (be “used” to) account for such possibilities? To answer the second question, we need to stop seeing the computer as a “means” (i.e. we “use” a computer) and to start thinking about the computer itself as a part of the literary process. This is perhaps to blur the distinction between e-literature and media studies on the one hand, and digital humanities on the other. However, it presupposes that technology is not something to be feared (as “tampering” with the text), but that it is rather something intrinsic, to be conceived on its own terms. Indeed, the computer can enhance the literary experience and highlight aspects of the text that were not noticed before, and vice versa, in a sort of feedback circuit, bringing with it hermeneutic questions that hitherto have been only indirect. What might we discover from exploring the symbiotic relationship between the text and the machine and about the minds and bodies that encounter these? Such encounters occur not only through visualization, but through sonorization and through the body. Such hybrid encounters require a broader view of language than that provided by information theory, which has apparently dominated digital literary studies. I will use my own digital humanities project on the visualization of French poet Stéphane Mallarmé’s works (http://mallarme.uvic.ca) to explore models of reading the digital

Computational Models (of Narrative) for Literary Studies

In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an important topic of investigation in both these areas, a more comprehensive approach coupling them with narratology, digital humanities and literary studies was still lacking. With the aim of covering this empty space, in the last years, a multidisciplinary effort has been made in order to create an international meeting open to computer scientist, psychologists, digital humanists, linguists, narratologists etc.. This event has been named CMN (for Computational Models of Narrative) and was launched in the 2009 by the MIT scholars Mark A. Finlayson and Patrick H. Winston1

The LitOLAP Project: Data Warehousing with Literature

The litOLAP project seeks to apply the Business Intelligence techniques of Data Warehousing and OLAP to the domain of text processing (specifically, computer-aided literary studies). A literary data warehouse is similar to a conventional corpus, but its data is stored and organized in multidimensional cubes, in order to promote efficient end-user queries. An initial implementation exists for litOLAP, and emphasis has been placed on cube-storage methods and caching intermediate results for reuse. Work continues on improving the query engine, the ETL process, and the user interfaces

The stuff of science fiction : an experiment in literary history

Funding: Social Sciences and Humanities Research Council of CanadaThis article argues for a speculative, exploratory approach to literary history that incorporates information visualization early on into, and throughout, the research process. The proposed methodology combines different kinds of expertise—including that of fans and scholars in both literary studies and computer science—in processing and sharing unique cultural materials. Working with a vast fan-curated archive, we suggest tempering scholarly approaches to the history of science fiction (SF) with fan perspectives and demonstrate how information visualization can be incorporated into humanistic research processes, supporting exploration and interpretation of little-known cultural collections.PostprintPeer reviewe

Automatic Detection of Reuses and Citations in Literary Texts

For more than forty years now, modern theories of literature (Compagnon, 1979) insist on the role of paraphrases, rewritings, citations, reciprocal borrowings and mutual contributions of any kinds. The notions of intertextuality, transtextuality, hypertextuality/hypotextuality, were introduced in the seventies and eighties to approach these phenomena. The careful analysis of these references is of particular interest in evaluating the distance that the creator voluntarily introduces with his/her masters. Phoebus is collaborative project that makes computer scientists from the University Pierre and Marie Curie (LIP6-UPMC) collaborate with the literary teams of Paris-Sorbonne University with the aim to develop efficient tools for literary studies that take advantage of modern computer science techniques. In this context, we have developed a piece of software that automatically detects and explores networks of textual reuses in classical literature. This paper describes the principles on which is based this program, the significant results that have already been obtained and the perspectives for the near future