Quantitative Drama Analytics: Tracking Character Knowledge (Q:TRACK)

• Applicant: Professor Dr. Nils Reiter, since 3/2021
• Subject Area: German Literary and Cultural Studies (Modern German Literature) ; General and Comparative Linguistics, Experimental Linguistics, Typology, Non-European Languages
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 424244162

Ever since, dramatic plays were based on social relations, especially on family relations. Asymmetric distributions of knowledge about these relations are the main motivation for dramatic action (mythos) and dramatic effects. Research has repeatedly paid attention to this, but only in terms of small units as singular plays or oeuvres. Besides those close reading efforts there is still no attempt to investigate character knowledge about social relations in drama on a bigger scale. In Q:TRACK we aim at closing this gap by connecting techniques and methods from computational linguistics and digital humanities with the in-depth knowledge of literary studies about drama history and poetics.The first objective is situated in literary and drama history. By analysing a corpus of more than 600 plays we will quantify and specify the interconnections between social relations and dramatic conflicts throughout drama history. More precisely, we investigate when and how this social knowledge is transferred between characters. Real, merely assumed, or undisclosed social relations give reason to the dramatic interaction of the involved characters, which in turn also constitutes social relations.The second objective is to operationalize knowledge dissemination in the fictional worlds of drama. As it is the most important kind of knowledge in drama, we focus on social knowledge, i.e., knowledge about social relations between characters (“Orest is the brother of Elektra”). The technical and methodological aim is to develop annotation guidelines for instances of knowledge distribution and subsequently to detect such instances automatically within the dramatic text. With this, we will track the social knowledge for each character over the course of the play. In addition, we aim at extending the corpus base for quantitative drama research with methods for the semi-automatic detection of dramatic structure.The motivation for this undertaking is the relevance of character knowledge for their comprehension as literary beings. In particular, asymmetries and changes of knowledge that literary characters have (or don’t have) about the social relations in ‘their’ fictional worlds are constitutive for dramatic effect theories (catharsis) since antiquity. In comedy, confusing characters became genre-forming and led via Shakespeare to the "Comedy of errors" ("Verwechslungskomödie"). In tragedy, the oldest and most popular twists of mythos (peripeteia) are closely linked to the knowledge characters have about themselves or others (esp. anagnorisis).Therefore, the distribution and dissemination of social knowledge within the 'small world' of a play is central to our understanding as readers and researchers. Q:TRACK pilots the computational analysis of this knowledge by focusing on unambiguously defined and processable forms of knowledge.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2207: Computational Literary Studies
• Ehemaliger Antragsteller: Dr. Marcus Willand, until 2/2021