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

SBE-UKRI：通过定性表征、推理和可视化理解叙事中不精确的空间和时间

基本信息

批准号：
ES/W003473/1
负责人：
Ian Gregory
金额：
$ 103.8万
依托单位：
Lancaster University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FW003473%2F1
关键词：
SBE UKRI Understanding imprecise space

项目摘要

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.

人类经验主要是以文本的形式记录和交流的，这些文本越来越多地以数字语料库的形式出现。社会科学、人文科学和计算机科学的研究人员面临的一个主要挑战是如何在跨学科环境中使用这些文本，以发展对所描述经验的连贯理解。近年来，在地理信息科学(GISC)、语料库语言学、自然语言处理(NLP)、人文地理学、文学研究和数字人文等不同领域，理解文本来源中的地理信息引起了大量研究兴趣。目前的技术水平涉及使用地理搜索来自动识别文本中的地名，并将其分配到坐标(Grover等人，2010)。一旦以这种方式进行地理参考，地名就可以读入地理信息系统进行测绘和空间分析。还可以使用语料库语言学和自然语言处理技术进行分析，以确定哪些单词或主题与地名有关，如地名与美丽或引发恐惧等情感反应有关。这种方法的组合被称为地理文本分析(GTA)(Gregory等人，2015)。虽然GTA为理解语料库中的地理位置提供了一个有用的起点，但它是高度定量的，仅限于可以找到坐标的指定地点，并且几乎没有时间概念。然而，正如对旅程的叙述充分表明的那样，人类对地理的体验更多地是主观的，更适合定性的表现。在这些情况下，“地理”不限于指定的地点；相反，它包括模糊、不精确和模棱两可的词，例如，“营地”、“远处的山”或“更远的路”，并包括使用诸如“近”、“在左边”或“几个小时的路程”等术语的相对位置。这些定性表示是必要的上下文参照，但不能在地理空间技术(如地理信息系统)中进行管理。为了在大范围内理解人类描述和与周围世界相关的方式，我们需要能够以视觉的方式表示和解释作者所描述的地理，这种方式将所描述的空间经验的定性性质与使它们可以定量分析的方法相结合。借助一个强大的跨学科团队，这笔赠款将开发出允许我们识别、提取、可视化和分析对地点和时间的定性和定量参考的方法。这些方法将被用于分析两个大型语料库：一个是关于英国湖区的旅行写作语料库，主要写于18世纪和19世纪；另一个是大屠杀幸存者证词语料库。尽管这两个语料库分别基于非常不同的旅行类型--休闲旅行和被迫迁徙--但这两个语料库代表了一组独特的声音，它们融合在一起，产生了复杂的文化和体验地理。该项目将探索来自自然语言处理、语料库语言学、定性时空推理(QSTR)、GISC和视觉分析的尖端数字技术如何帮助我们理解作者自己如何表示他们周围的地理，并探索这些文本所包含的地域感和经验的个体和聚合表示。由此产生的应用程序对学术界和非学术界的受众都将具有重要意义。