SBE-UKRI: Understanding imprecise space and time in narratives through qualitative representations, reasoning, and visualisation

Human experiences are recorded and communicated mostly as text which are increasingly available as digital corpora. A major challenge for researchers in the social sciences, humanities and computer sciences is how to use these texts in interdisciplinary settings to develop cohesive understandings of the experiences described. Understanding geographies in textual sources has received a significant amount of research interest in recent years across fields as diverse as geographical information science (GISc), corpus linguistics, natural language processing (NLP), human geography, literary studies, and digital humanities. The current state of the art involves using geoparsing to automatically identify the place names in texts and allocate them to a coordinate (Grover et al 2010). Once georeferenced in this way, place names can be read into a geographical information system for mapping and spatial analysis. Analysis can also be conducted using techniques from corpus linguistics and NLP to see what words or themes are associated with the place name such as the place being associated with emotional responses such as being beautiful or inspiring fear. This combination of approaches is known as geographical text analysis (GTA) (Gregory et al 2015).

While GTA provides a useful starting point for understanding the geographies within a corpus, it is highly quantitative, is limited to named places for which coordinates can be found, and has little concept of time. Yet, as narratives of journeys make abundantly clear, human experiences of geography are more often subjective and more suited to qualitative representation. In these cases, "geography" is not limited to named places; rather, it incorporates the vague, imprecise, and ambiguous, with references to, for example, "the camp", "the hills in the distance", or "further down the road", and includes the relative locations using terms such as "near to", "on the left", or "a few hours' journey" from. These qualitative representations are necessary contextual referents but cannot be managed within geospatial technologies such as GIS. To understand on a large scale the ways in which humans describe and relate to the world around them, then, we need to be able to visually represent and interpret the geographies authors describe in ways that combine the qualitative nature of described spatial experiences with methods that render them quantitatively analysable.

Drawing on a strongly interdisciplinary team, this grant will develop approaches that allow us to identify, extract, visualise, and analyse qualitative and quantitative references to place and time. These methods will be applied to analyses of two large corpora: one a corpus of travel writing about the English Lake District, predominantly written in the 18th and 19th centuries; the other, a corpus of Holocaust survivor testimonies. Although based on very different types of journey - leisure travel and forced migration respectively - both corpora represent a collection of unique voices that coalesce to generate complex cultural and experiential geographies. The project will explore how cutting-edge digital technologies from NLP, corpus linguistics, Qualitative Spatio-Temporal Reasoning (QSTR), GISc, and visual analytics can help us understand how authors themselves represented the geographies that surrounded them and explore the individual and aggregate representation of the sense and experience of place that these texts contain. The resulting applications will have great significance for scholarly and non-academic audiences alike.