Elements in Digital Literary Studies – serie

Our analysis of over 20,000 books published in Britain between 1800 and 2009 compares the geographic attention of fiction authored by women and by men; of books that focus on women and men as characters; and of works published in different eras. We find that, while there were only modest differences in geographic attention in books by men and women authors, there were dramatic geographic differences in books with highly gendered character space. Counter to expectation, the geographic differences between differently gendered characters were remarkably stable across these centuries. We also examine and complicate the power attributed to separate-sphere ideology. And we demonstrate a surprising reversal of critical expectation: in fiction, broadly natural spaces were more strongly associated with men, while urban spaces were more aligned with women. As it uncovers spatial patterns in literary history, this study casts new light on well-known texts and reimagines literature's broader engagement with gender and geography.

This Element sheds a new light on the ubiquitous yet complex notion of mimesis. By systematically comparing the social dynamics of the Dutch population at a given time with the social dynamics of characters in Dutch literary fiction published in the same period, it aims to pinpoint the ways in and the extent with which literary fiction either mirrors or shapes the societal context from which it emerged. While close-reading-based scholarship on this topic has been limited to qualitative interpretations of allegedly exemplary works, the present study uses the data-driven tools of social network analysis to systematically determine the imitative elements of the social dynamics of characters within larger-scale, representative collections of books of literary fiction.

The Challenges of Born-Digital Fiction: Editions, Translations, and Emulations addresses the growing concern about how best to maintain and extend the accessibility of early interactive novels and hypertext fiction or narratives. These forms of born-digital literature were produced before or shortly after the mainstreaming of the World Wide Web with proprietary software and on formats now obsolete. Preserving and extending them for a broad study by scholars of book culture, literary studies, and digital culture necessitate they are migrated, translated, and emulated - yet these activities can impact the integrity of the reader experience. Thus, this Element centers on three key challenges facing such efforts: (1) precision of references: identifying correct editions and versions of migrated works in scholarship; (2) enhanced media translation: approaching translation informed by the changing media context in a collaborative environment; and (3) media integrity: relying on emulation as the prime mode for long-term preservation of born-digital novels.

Sentiment analysis has gained widespread adoption in many fields, but not-until now-in literary studies. Scholars have lacked a robust methodology that adapts the tool to the skills and questions central to literary scholars. Also lacking has been quantitative data to help the scholar choose between the many models. Which model is best for which narrative, and why? By comparing over three dozen models, including the latest Deep Learning AI, the author details how to choose the correct model-or set of models-depending on the unique affective fingerprint of a narrative. The author also demonstrates how to combine a clustered close reading of textual cruxes in order to interpret a narrative. By analyzing a diverse and cross-cultural range of texts in a series of case studies, the Element highlights new insights into the many shapes of stories.

This Element reconsiders what the focus of digital literary mapping should be for English Literature, what digital tools should be employed, and to what interpretative ends. How can we harness the digital to find new ways of understanding spatial meaning in the Humanities? The Element elucidates the relationship between literature, geography, and cartography and the emergence of literary mapping, providing a critique of current digital methods and making the case for new approaches. It explores the potential of Mikhail Bakhtin's 'chronotope' as a way of structuring digital literary maps that provides a solution to the complexities of mapping time and space. It exemplifies the method by applying it first as one of two approaches to mapping the realist novel by way of Dickens, and then to the multiple states of J. M. Barrie's Peter Pan. This title is also available as Open Access on Cambridge Core.

This Element reconsiders what the focus of digital literary mapping should be for English Literature, what digital tools should be employed, and to what interpretative ends. How can we harness the digital to find new ways of understanding spatial meaning in the Humanities? The Element elucidates the relationship between literature, geography, and cartography and the emergence of literary mapping, providing a critique of current digital methods and making the case for new approaches. It explores the potential of Mikhail Bakhtin's 'chronotope' as a way of structuring digital literary maps that provides a solution to the complexities of mapping time and space. It exemplifies the method by applying it first as one of two approaches to mapping the realist novel by way of Dickens, and then to the multiple states of J. M. Barrie's Peter Pan. This title is also available as Open Access on Cambridge Core.

Deep maps capture complex relationships to place and help trace the relationship between the abstract spaces of traditional maps and the cultural and literary history of the places that they represent. Using early modern Ireland as a template, this Element explores how deep-mapping techniques and a decolonial data ethic can be used to assemble a more culturally and linguistically representative archive and create more inclusive literary histories. It shows how deep mapping can disrupt colonial teleology and counter the monophone (and, specifically, anglophone) colonial record by bringing the long-neglected voices of the colonised back into the conversation. In doing so, it recovers a pre-conquest cultural vibrancy which colonisation, the language shift from Irish to English, and scholarly inattention successively occluded. More broadly, it offers a model for engaging with decolonial literary deep maps by developing reading strategies for 'juxtapuntal' reading that has the potential to decolonise the canon.

Deep maps capture complex relationships to place and help trace the relationship between the abstract spaces of traditional maps and the cultural and literary history of the places that they represent. Using early modern Ireland as a template, this Element explores how deep-mapping techniques and a decolonial data ethic can be used to assemble a more culturally and linguistically representative archive and create more inclusive literary histories. It shows how deep mapping can disrupt colonial teleology and counter the monophone (and, specifically, anglophone) colonial record by bringing the long-neglected voices of the colonised back into the conversation. In doing so, it recovers a pre-conquest cultural vibrancy which colonisation, the language shift from Irish to English, and scholarly inattention successively occluded. More broadly, it offers a model for engaging with decolonial literary deep maps by developing reading strategies for 'juxtapuntal' reading that has the potential to decolonise the canon.

The Challenges of Born-Digital Fiction: Editions, Translations, and Emulations addresses the growing concern about how best to maintain and extend the accessibility of early interactive novels and hypertext fiction or narratives. These forms of born-digital literature were produced before or shortly after the mainstreaming of the World Wide Web with proprietary software and on formats now obsolete. Preserving and extending them for a broad study by scholars of book culture, literary studies, and digital culture necessitate they are migrated, translated, and emulated - yet these activities can impact the integrity of the reader experience. Thus, this Element centers on three key challenges facing such efforts: (1) precision of references: identifying correct editions and versions of migrated works in scholarship; (2) enhanced media translation: approaching translation informed by the changing media context in a collaborative environment; and (3) media integrity: relying on emulation as the prime mode for long-term preservation of born-digital novels.

Our analysis of over 20,000 books published in Britain between 1800 and 2009 compares the geographic attention of fiction authored by women and by men; of books that focus on women and men as characters; and of works published in different eras. We find that, while there were only modest differences in geographic attention in books by men and women authors, there were dramatic geographic differences in books with highly gendered character space. Counter to expectation, the geographic differences between differently gendered characters were remarkably stable across these centuries. We also examine and complicate the power attributed to separate-sphere ideology. And we demonstrate a surprising reversal of critical expectation: in fiction, broadly natural spaces were more strongly associated with men, while urban spaces were more aligned with women. As it uncovers spatial patterns in literary history, this study casts new light on well-known texts and reimagines literature's broader engagement with gender and geography.

This Element tackles the problem of generalization with respect to text-based evidence in the field of literary studies. When working with texts, how can we move, reliably and credibly, from individual observations to more general beliefs about the world? The onset of computational methods has highlighted major shortcomings of traditional approaches to texts when it comes to working with small samples of evidence. This Element combines a machine learning-based approach to detect the prevalence and nature of generalization across tens of thousands of sentences from different disciplines alongside a robust discussion of potential solutions to the problem of the generalizability of textual evidence. It exemplifies the way mixed methods can be used in complementary fashion to develop nuanced, evidence-based arguments about complex disciplinary issues in a data-driven research environment.