Reclaiming the 'Golden Age': The Second Person in Digital Fiction

Since the demise of the 'Golden Age' of literary hypertext (Coover 1999) and the theoretical debates surrounding online and offline electronic literature that followed in its wake, the study of digital fiction in particular has undergone a significant paradigm shift. Recent research has moved from a 'first-wave' of pure theoretical debate to a 'second-wave' of close stylistic and semiotic analysis. While the theoretical intricacies of second-wave digital fiction theory have been well debated (e.g. Ciccoricco 2007, Ensslin 2007, Ensslin and Bell 2007, Bell 2010 forthcoming), the discipline and practice of close-reading digital fiction require a more systematic engagement and understanding than offered by previous scholarship. With this in mind, the Digital Fiction International Network ('DFIN', funded by The Leverhulme Trust since January 2009) has been exploring new avenues of defining and implementing approaches to close-reading, with the tripartite trajectory of developing a range of tools and associated terminology for digital fiction analysis; of providing a body of analyses based on the close-reading of texts, which are substantiated by robust theoretical and terminological conclusions; and of fostering a collaborative network of academics working on inter-related projects.

In following this agenda, this paper offers a comparative approach to second person narration in two exemplary digital fictions: geniwate and Deena Larsen’s satirical flash fiction, The Princess Murderer (2003), and Jon Ingold's interactive fiction mystery, All Roads (2006 [2001]). We aim to explore the extent to which print-oriented narratological approaches to the textual 'You' (e.g. Herman 1994) apply to the texts under investigation and suggest theoretical tenets arising from their distinct (inter-)medial and ludic qualities (cf. Ryan 1999). Of particular interest will be the ways in which the reader and his/her role in the cybernetic feedback loop are constructed textually and interactionally.

(Source: Authors' abstract for ELO_AI)