Structuring Literature: Variants and Functions of Reflective Passages in Narrative Fiction

“所有幸福的家庭都是相似的，每个不幸的家庭都有自己的不幸。”这是托尔斯泰《安娜·卡列尼娜》的第一句话，也是虚构文学中最为人津津乐道的反思例子之一。虽然即使是外行人也会将小说中的这种反思性段落与报道行为或描述人物的段落区分开来，但反思性段落在文学研究中还没有被确立为一个独立的研究课题。在此背景下，该项目将结合联合收割机的见解，从文学研究，语言学，计算建模和定量以及定性文本分析（i）阐述和正式化的反思通道的综合概念，（ii）识别和分类叙事小说中的反思通道和（iii）解释其发生模式在大约350年的文学史。为此，该项目将建立在以前的工作，以自动识别其他文本类型中的反射，以及检测相关现象的工作，如泛型和认知状态，并在语言学上知情的机器学习框架中扩展和联合收割机这些，以寻找叙事小说中的作者/叙述者属性和人物属性的反射段落。通过将我们的模型应用于跨越几个世纪的德国文学的大型语料库，我们将能够确定反思特别普遍的时期（“繁荣时期”）。我们还将更仔细地研究文学史上反思性叙事的两个突出变体：散文式叙事和非传统叙事。我们将比较自动识别的散文和散文的叙事小说，非虚构的散文和散文的文本和调查的相似性和差异方面的风格，主题和认识状态的条款，以确定内部以及外部功能的这些段落的文学作品和他们的社会文化背景。 我们对整体优先项目“计算文学研究”的贡献在于（i）通过进行定性和定量的语料库研究，从文学理论中操作一个基本概念，（ii）丰富结构文学文本的方法选择，（三）开发新的计算模型来检测反射和相关现象，并证明这些算法方法对文学史学的有用性将其结果整合到定性研究过程中，以及（iv）创建和发布一个人工注释的语料库以供反思。

"All happy families are alike, each unhappy family is unhappy in its own way," is the first sentence of Tolstoy's "Anna Karenina" and one of the most talked about examples of reflection in fictional literature. Although even lay people distinguish such reflective passages in novels from passages that report actions or describe characters, reflective passages have not yet been established as a research topic in their own right in literary studies. Against this backdrop the project will combine insights from literary studies, linguistics, computational modelling and quantitative as well as qualitative text analysis to (i) elaborate and formalise a comprehensive concept of reflective passage, (ii) identify and classify such reflective passages in narrative fiction and (iii) explain their patterns of occurrence in roughly 350 years of literary history. To this end, the project will build on previous work for identifying reflection automatically in other text types as well as work on detecting related phenomena such as genericity and epistemic status and extend and combine these in a linguistically informed machine learning framework for finding author/narrator-attributed and character-attributed reflective passages in narrative fiction. By applying our models to a large corpus of German literature spanning several centuries, we will be able to identify periods in which reflection was particularly prevalent (“boom periods”). We will also look more closely at two prominent variants of reflective storytelling in literary history: essayistic and encyclopedic narration. We will compare automatically identified essayistic and encyclopedic passages in narrative fiction to non-fictional essays and encyclopedic texts and investigate similarities and differences with respect to style, topic and the epistemic status of clauses in order to identify internal as well as external functions of these passages in relation to the literary works and their socio-cultural context. Our contribution to the overall Priority Program “Computational Literary Studies” consists in (i) operationalizing a basic concept from literary theory by performing a qualitative and quantitative corpus study, (ii) enriching the methodic options to structure literary texts, (iii) developing novel computational models for detecting reflection and related phenomena and demonstrating the usefulness of these algorithmic methods for literary historiography as well as the integration of their results into the qualitative research process, and (iv) creating and releasing a corpus manually annotated for reflection.