Stories are complex webs connecting imaginary events and people, which are written and told to entertain. The corresponding art of conceiving the most entertaining plots in which these events and people play roles has not only been tackled by storytellers but has recently also been approached using computational means. Still, Computational Storytelling (CS) as a prominent subfield within Computational Creativity (CC) hitherto has mostly focused on planning stories and creating them with the help of text generation methods from Natural Language Processing (NLP), thus simulating a logically coherent plot. A good story, however, is much more than that. Relevant aspects also include narrative concepts like narrative style, chronology of narratives, focalization and perspective – which currently to most parts still lie beyond the horizon of CS. This does not hold for every discipline, though: These narratological concepts have been investigated by literary scholars for a long time.

Digital methods, in turn, have recently been of interest as an approach towards literature analysis, often referred to as Digital Literary Studies (DLS). Yet, operationalization of these well-understood concepts is required when used as the basis for computational modelling – a challenge that is often taken up in collaborations between researchers from NLP and the Literary Studies. The process of making concepts explicit enough to operationalize them can in turn sharpen the definitions of theoretical considerations and feed back into theoretical discussions.

These are just a few of the obvious meeting points between CC/CS and NLP and between NLP and DLS. However, these connections are not (yet) transitive. The goal of this Dagstuhl Seminar is to overcome the current divisions and establish links between all three disciplines and among involved researchers.

The potential benefits for the respective fields include:

• One of the major challenges in DLS is the approximation of concepts with computational approaches (i.e. their operationalization) which not only requires a translation of the concepts, but also a deep understanding of the deployed computational approaches used. This gap can best be tackled by providing expertise from the fields concerned. Whereas NLP is already accepted as such a field (but still needed), CS has not been taken into consideration yet. Additionally, a second type of collaboration that still needs to be intensified is the one that connects the interpretative, manual annotations from DLS with computational approaches to text analysis and generation.
• In its early days, NLP has focused on a limited variety of texts and consequently suffers from a bias towards newspaper texts. Even though there are efforts towards more diverse and flexible text processing, the constant lack of data is a hindering factor. Digital Humanities (DH) and CC offer varieties of texts (and the potential means to generate further examples) mitigating the impasse.
• In CC, CS focuses almost exclusively on plot and logical structure of storytelling. However, as mentioned before, a narrative is a complex web of different factors that are well-investigated in classical disciplines. While much work is based on formalist theories about narrative, other approaches from narrative theory still need to be explored better. For example, CS could benefit from the well-established fields of semiotics and structuralism as well as from more recent, reader-oriented developments in cognitive and empirical narratology.

In short, establishing the suggested links promises significant advantages for each of the involved fields, as all three focus on the same object of investigation. Among others, each community can gain insights into how to improve their own methods and findings without necessarily fully unifying the respective research fields. Bringing together both thought leaders and young aspiring researchers from the relevant communities, the seminar creates the necessary environment to establish professional and personal ties, forming the foundation for the required collaborations across disciplinary boundaries.

Creative Commons BY 3.0 DE

Tarek Richard Besold, Pablo Gervás, Evelyn Gius, and Sarah Schulz

• Leonid Berov (Universität Osnabrück, DE) [dblp]
• Tarek Richard Besold (Telefonica Innovacion Alpha - Barcelona, ES) [dblp]
• Amilcar Cardoso (University of Coimbra, PT) [dblp]
• João Miguel Cunha (University of Coimbra, PT) [dblp]
• Thierry Declerck (DFKI - Saarbrücken, DE) [dblp]
• Mark Finlayson (Florida International University - Miami, US) [dblp]
• Pablo Gervás (Complutense University of Madrid, ES) [dblp]
• Evelyn Gius (TU Darmstadt, DE) [dblp]
• Marina Grishakova (University of Tartu, EE)
• Christian Guckelsberger (Queen Mary University of London, GB) [dblp]
• Christopher Hench (Amazon - Cambridge, US) [dblp]
• Jonas Kuhn (Universität Stuttgart, DE) [dblp]
• Kai-Uwe Kühnberger (Universität Osnabrück, DE) [dblp]
• Oliver Kutz (Free University of Bozen-Bolzano, IT) [dblp]
• Carlos León (Complutense University of Madrid, ES) [dblp]
• Rafael Pérez y Pérez (Universidad Autonoma Metropolitana - Cuajimalpa, MX) [dblp]
• Enric Plaza (CSIC - Bellaterra, ES) [dblp]
• Manuel Portela (Universidade de Coimbra, PT) [dblp]
• Dino Pozder (University of Tartu, EE)
• Nils Reiter (Universität Stuttgart, DE) [dblp]
• Sarah Schulz (Ada Health - Berlin, DE) [dblp]
• Hannu Toivonen (University of Helsinki, FI) [dblp]
• Sara L. Uckelman (Durham University, GB) [dblp]
• Tony Veale (University College Dublin, IE) [dblp]
• Philipp Wicke (University College Dublin, IE) [dblp]
• Sina Zarrieß (Universität Bielefeld, DE) [dblp]