Diversity at the thematic and methodological level
The projects of the Digital Humanities department cover a wide range of topics: From editing to stylometric, narratological, linguistic and social science issues.
Such a diversity of domains and data also requires a variety of approaches. Therefore, projects of both the employees as well as those of student groups from the project seminars are characterized by very different methods. Text statistical methods for style and topic analysis are used as well as database modeling and simulation.
Staff: Gabriel Viehhauser
The project deals with the digital modelling of spatial constructions in narrative texts. The category of space has so far received little attention in narratology, although the location of a narrative is a central element similar to the characters or the plot. In Yuri Lotman's approach to spatial semantics, it becomes especially clear that spaces often have a meaning of their own, e.g. the forest is often the sphere of monsters and fairies and stands in contrast to the city, castle or civilisation. The border between these spaces can usually only be crossed by the hero; so it becomes clear how in Lotman's approach figures, event and plot belong together.
On the one hand, digital modeling of this semantics of space presents a methodical challenge, since spaces in narratives are, to a large extent, also implicitly created and are difficult for the computer to grasp. On the other, it is precisely the need to specify the models that the computer requires which can bring a narratological gain in knowledge. We are currently concentrating on network analyses of various texts, but, above all, on Ovid's Metamorphoses in order to visualise the network relationship between the entities of space, figures and events.
Staff: Malte Heckelen
The dissertation project is focused on the one hand on polarization as a mass phenomenon and on the other on cognitive assumptions from persuasion research. People use mental heuristics to, for instance, break down the complexity of a topic and, possible due to time pressure (or low interest), to be able to make a judgement or decision quickly. Such phenomena are related to individual polarization and social influence through various pathways. The project is focused on describing the relation of individual polarization to polarization as a mass phenomenon through empirical analysis as well as simulation.
In social psychology and political science, effects of mental heuristics on persuasion and polarization are primarily researched through individual or small group experiments. Certain effect patterns are visible, but the strength and direction of these effects varies considerably. This could be due to small samples and the various, highly interactive predictors. However, communication is subject to norms like any other social phenomenon. These peer group norms possibly also exert influence on the way an individual is (subconsciously) predispositioned to the usage of mental heuristics and related tools in certain scenarios. It might also factor in decisions on which communications are considered more valid and persuasive (e.g. some communities may find communications from the same group more persuasive than scientific evidence).
To research this, a sociologically oriented decision model is constructed, in which individuals base their communicative decisions on their knowledge of peer group communicative behavior. This model serves as a theoretical underpinning for the empirical analysis of Twitter data. This data is gathered on various connected communities and their discussions of various topics over time. To relate the more individual-focused decision model to large-scale implications, an agent-based model will be constructed.