Reading concordances in the 21st century (RC21)

在当今的数字世界中，以电子形式传达的文本量不断增加，并且越来越需要从文本中大规模提取含义的方法和途径。语料库语言学家长期以来一直在研究数字化文本，并确定了许多语言的特征是重复出现的模式。因此，“眼睛”这个词可以与“奶油”和“测试”这样的词一起出现，或者像“关闭”和“固定”这样的词。在语料库语言学中，这种模式是在索引的帮助下识别的，即以紧凑的格式显示一个词、短语或结构在一系列上下文中的多次出现。然而，由于缺乏一个完善和明确的方法，阅读索引的艺术尚未实现其全部潜力。与此同时，语料库语言学家可用的检索软件包在算法上几乎没有创新。本项目提出了一种21世纪世纪阅读检索的创新方法。通过伯明翰大学和埃尔兰根-纽伦堡大学之间的合作，我们将联合收割机在语料库语言学理论工作中的优势与计算算法的专业知识相结合，以开发一种系统的方法来进行阅读索引。我们将开发工具独立的战略和相应的算法的半自动组织的一致性线，并实现它们在软件中的concept。为了开发和测试我们的方法，我们将进行两个案例研究。第一个将集中在身体语言的小说相比，非小说文本。第二个将专注于社会媒体中的政治论证，将其结果形式化为可用于自动论证挖掘的语料库查询。这两个案例研究包括英语和德语之间的比较维度。因此，他们拓宽了一致性阅读的方法，这些方法到目前为止一直非常关注英语。通过这些案例研究，我们将建立一种方法，不仅提供语料库语言学的创新，但也有更广泛的影响，在规模的文本数据的分析，同时仍然保留人文的角度。我们将开发的CNOConc作为开源软件，使其他研究人员可以使用它作为一个现成的工具，或将其集成到现有的索引工具或自己的软件环境。这两个conclusionconc和我们的工具独立的方法，以一致性分析将有相关性超越语料库语言学，提供创新的方法和算法的学科，如数字人文和计算社会科学。我们将以各种形式提高人们对新的可能性的认识，例如，通过一个项目博客，我们的软件用户可以分享他们的经验，并在一个由国际领先专家组成的咨询委员会的帮助下。我们将在暑期学校和会议上举办培训班，并在网上提供教育材料。

In today's digital world, the amount of text communicated in electronic form is ever-increasing and there is a growing need for approaches and methods to extract meanings from texts at scale. Corpus linguists have long been studying digitised texts and have established that much of language is characterised by recurring patterns. So the word 'eye' can appear together with words like 'cream' and 'test', or words like 'closed' and 'fixed'. In corpus linguistics, such patterns are identified with the help of concordances, i.e. displays that show many occurrences of a word, phrase or construction across a range of contexts in a compact format. However, lacking a well-established and clear-cut methodology, the art of reading concordances has not yet realised its full potential. At the same time, there has been very little innovation in algorithms in the concordance software packages available to corpus linguists.This project proposes an innovative approach to reading concordances in the 21st century. Through the collaboration between the University of Birmingham and FAU Erlangen-Nürnberg we combine strengths in theoretical work in corpus linguistics with expertise in computational algorithms in order to develop a systematic methodology for reading concordances. We will develop tool-independent strategies and corresponding algorithms for the semi-automatic organisation of concordance lines, and implement them in the software FlexiConc. To develop and test our approach, we will conduct two case studies. The first will focus on body language in fiction compared to non-fiction texts. The second will focus on political argumentation in social media, formalising its findings as corpus queries that can be used for automatic argumentation mining. Both case studies include a comparative dimension between English and German. Hence, they broaden out approaches to concordance reading which have been very focused on the English language so far. Through these case studies, we will establish an approach that not only provides innovation in corpus linguistics, but also has wider implications for the analysis of textual data at scale, while still retaining a humanities perspective.We will develop FlexiConc as open-source software, so that other researchers can use it as an off-the-shelf tool or integrate it into existing concordance tools or their own software environment. Both FlexiConc and our tool-independent approach to concordance analysis will have relevance beyond corpus linguistics, providing innovative approaches and algorithms for disciplines such as digital humanities and computational social science. We will raise awareness of the new possibilities in a variety of forms, for instance, through a project blog where users of our software can share their experience, and with the help of an advisory board of leading international experts. We will run training sessions at summer schools and conferences and make educational materials available online.