Extracting Social Network from Literary Prose

This thesis develops an approach to extract social networks from literary prose, namely, Jane Austen’s published novels from eighteenth- and nineteenth- century. Dialogue interaction plays a key role while we derive the networks, thus our technique relies upon our ability to determine when two characters are in conversation. Our process involves encoding plain literary text into the Text Encoding Initiative’s (TEI) XML format, character name identification, conversation and co-occurrence detection, and social network construction. Previous work in social network construction for literature have focused on drama, specifically manually TEI-encoded Shakespearean plays in which character interactions are much easier to track in due to their dialogue-driven narrative structure. In contrast, prose is structured quite differently; character speeches are not very clearly formatted, making it more difficult to assign specific dialogue to each character. We implement two different parsing strategies based on context size (chapter scope and paragraph scope) to detect character interactions. To check the accuracy of our methods, we conduct one evaluation that is based on network statistics and another evaluation that involves measuring similarity (edit distance) between the networks constructed from manually encoded novels versus our constructed graphs. Our findings suggest that the choice of context size is non-trivial and can have a substantial influence on the resulting networks. In general, the paragraph level interaction approach seemed to be more accurate

DH Benelux Journal 1. Integrating Digital Humanities.

The first volume of the DH Benelux Journal. This volume includes four full-length, peer-reviewed articles that are based on accepted contributions to the 2018 DH Benelux conference in Amsterdam (The Netherlands) on Integrating Digital Humanities. Contents: 1. Editors' Preface (Wout Dillen, Marijn Koolen, Marieke van Erp) 2. Introduction: Integrating Digital Humanities (Julie Birkholz and Gerben Zaagsma) 3. Boundary practices of digital humanities collaborations (Max Kemman) 4. Manuscripts, Metadata, and Medieval Multilingualism: Using a Manuscript Dataset to Analyze Language Use and Distribution in Medieval England (Krista A. Murchison and Ben Companjen) 5. Analysis of Fidel Castro Speeches Enhanced by Data Mining (Sergio Peignier and Patricia Zapata) 6. Character Centrality in Present-Day Dutch Literary Fiction (Roel Smeets, Eric Sanders, and Antal van den Bosch

Character Constellations

Fiction has a major social impact, not least because it co-shapes the image that society has of various social groups. Drawing on a collection of 170 contemporary Dutch-language novels, Character Constellations presents a range of data-driven, statistical models to study depictions of characters in terms of gender, race, ethnicity, class, age, sexuality, and other identity categories. Incorporating the tools of network analysis, each chapter highlights an aspect of fictional social networks that affects the representation of social groups: their centrality, their communities, and their conflicts. While reading individual novels in light of emerging statistical patterns, combining the formal methods of social network analysis with the interpretive tools of narratology, this study shows how central societal themes such as (in)equality and emancipation, integration and segregation, and social mobility and class struggle are foregrounded, replicated, or distorted in the Dutch novel. Showcasing what character-based critiques of literary representation gain by integrating data-driven methods into the practice of critical close reading, Character Constellations contributes to societal debates on cultural representation and identity and the role fiction and art have in those debates