Methodology and Reflection: Linguistic Discourse Historiography as Digitally Supported Group Research (Methodological Cross-Sectional Project)

数字话语分析需要人工解释学和算法程序相互驱动知识的过程。从方法论的角度来看，课题组“争议性话语”。自1990年以来，《作为当代史的语言史》将自己整体视为理解话语史的协作方法的实验室。其目的是为符合语篇分析的质量标准和理论框架的解释性范畴的数字分析制定一个工作流程。这就提出了一些在该领域仍未解决的程序性问题，一方面涉及语用标注的质量标准，例如标注中切分、分类和解释深度之间的关系，另一方面涉及从研究问题到标注方案再到模式识别的双重可操作性步骤。次级项目7的目的是评价、反思和逐步优化研究小组的方法及其融入协作工作流程。这是通过中心研究问题来追求的：如何优化协作注释的过程，并开发适当的质量测量方法？为此，我们将对作为语篇语言学方法的注释进行系统的研究。这将汇集和系统化研究组的方法论成果，并对基于人工神经网络的分类器的使用进行实验。由于这种自反性和独一无二的方法论取向，子项目不会收集自己的研究数据，而是与其他子项目的新兴研究数据进行增量合作。这一背景的一个决定性优势是，这些程序性方法论问题可以与一个小组一起处理，在这个小组中，可以使用深厚的专业知识来构建其话语理论框架以及所有相关的定性和定量方法。

Digital discourse analysis requires procedures in which manual-hermeneutic and algorithmic procedures mutually drive the process of knowledge. From a methodological point of view, the research group “Controversial Discourses. Language History as Contemporary History since 1990” sees itself in its entirety as a laboratory of collaborative methods of an understanding discourse history. The aim is to develop a workflow for digital analyses of interpretative categories that meets the quality standards and theoretical framework of discourse analysis. This raises a number of procedural questions that are still unresolved in the field, concerning on the one hand the quality standards of pragmatic annotation, e.g. the relationship between segmentation, categorisation and depth of interpretation in annotation, and on the other hand the double operationalisation step from the research question to the annotation scheme to pattern recognition. The aim of sub-project 7 is to evaluate, reflect on and incrementally optimise the methods of the research group and their integration into a collaborative workflow. This is pursued by means of the central research question: How can processes of collaborative annotation be optimised and appropriate measurement methods of their quality be developed? To this end, a systematic study on “Annotation as a method of discourse linguistics” will be carried out. This will bring together and systematise the methodological findings of the research group and conduct experiments on the use of classifiers based on artificial neural networks. Because of this reflexive character and the exclusive methodological orientation, the sub-project will not collect its own research data, but will work incrementally with the emerging research data of the other sub-projects. A decisive advantage of this setting is that these procedural-methodological questions can be worked on with a group in which profound expertise is available for their discourse-theoretical framing as well as all relevant qualitative and quantitative methods.