The beginnings of modern poetry - Modeling literary history with text similarities

现实主义，19世纪的主要艺术形式，到20世纪初的早期现代主义的转变，被当时的同时代人和自那时以来的文学史视为影响许多形式和内容相关方面的深刻变化。诗歌也是如此。虽然今天只有一小部分诗人和诗歌被视为“现代”，但同时代的人将这一属性应用于更多的文本，例如，通过查看1900年左右出版的所有现代诗歌选集，可以看到。其中一个主要目标是理解这种差异：文学史是否忽视了其他诗歌中的现代趋势，还是当代人在没有变化和创新的情况下看到了变化和创新？为了回答这个问题，我们将看看文本的相似性，假设更多的现代文本彼此之间比更传统的文本更相似。相似性总是与特定的视角有关。当时的同时代人和今天的文学史学家认为现实主义诗歌和早期现代主义诗歌之间的主要区别在很大程度上是相同的：新的主题，新的形式以及在诗歌中表达和表达情感的新方式。我们将涵盖所有这些方面，但会以不同程度的努力来创新所使用的方法。新方法的发展将集中在语义文本相似度和情感或更精确的情感分析上。测量诗歌等短文本的文本相似度是相当具有挑战性的，但自从引入word2vec和其他形式的词嵌入以来，这种情况得到了显著改善。将这些方法应用于历史文本，特别是诗歌这样的体裁是另一个挑战：诗歌的词汇甚至与其他文学体裁相比也有明显的不同。它的特点是使用旧词和新词，其中许多是复合词。确定哪种词嵌入方法更适合我们的用例，以及如何使用它们来表示关注一般语义等维度的短文本是一个重点。另一个是历史情感词汇的发展，包括没有时代错误的情感。

The transition of realism, the dominant art form of the 19th Century, to early modernism at the turn to the 20th Century has been seen by contemporaries then and literary history since then as a profound change affecting many formal and content-related aspects. This is also true for poetry. But while today only a small group of poets and poems is seen as ‘modern’, the contemporaries applied this attribute to much more texts as can be seen, for example, by looking at all the anthologies with modern poetry published around 1900. One of the main goals is to understand this discrepancy: Does literary history ignore the modern trends in those other poems or did the contemporaries perceive change and innovation where there was none? In order to answer this question we will look at the similarity of texts, assuming that more modern texts will be more similar with each other than with more traditional texts. Similarity is always related to a specific perspective. The dimensions under which contemporaries then and literary historians today see the main differences between the poetry of realism and early modernism are mostly the same: new themes, new forms and a new way of addressing and expressing emotions in poems. We will cover all these aspects but with different degrees of effort to innovate the methods used. The development of new methods will concentrate on semantic text similarity and sentiment or more exact emotion analysis. Measuring the text similarity of short texts like poems is quite challenging, but since the introduction of word2vec and other forms of word embeddings the situation has improved dramatically. Applying these approaches to historical texts and especially to a genre like poetry is another challenge: The vocabulary of poetry is markedly different even compared to that of other literary genres. It is characterized by the usage of old-fashioned words and neologisms, many of which are compound words. Determining which approach to word embeddings is preferable for our use cases and how they can be used to represent short texts focusing on dimensions like general semantics is one focus. The other is the development of an historical sentiment lexicon including emotions without anachronism.