Creating the European Literary Text Collection (ELTeC): Challenges and Perspectives

Abstract

The aim of this contribution is to reflect on the process of building the multilingual European Literary Text Collection (ELTeC) that is being created in the framework of the networking project Distant Reading for European Literary History funded by COST (European Cooperation in Science and Technology). To provide some background, we briefly introduce the basic idea of ELTeC with a focus on the overall goals and intended usage scenarios. We then describe the collection composition principles that we have derived from the usage scenarios. In our discussion of the corpus-building process, we focus on collections of novels from four different literary traditions as components of ELTeC: French, Portuguese, Romanian, and Slovenian, selected from the more than twenty collections that are currently in preparation. For each collection, we describe some of the challenges we have encountered and the solutions developed while building ELTeC. In each case, the literary tradition, the history of the language, the current state of digitization of cultural heritage, the resources available locally, and the scholars' training level with regard to digitization and corpus building have been vastly different. How can we, in this context, hope to build comparable collections of novels that can usefully be integrated into a multilingual resource such as ELTeC and used in Distant Reading research? Based on our individual and collective experience with contributing to ELTeC, we end this contribution with some lessons learned regarding collaborative, multilingual corpus building.

Towards a computational history of modernism in European literary history: Mapping the Inner Lives of Characters in the European Novel (1840–1920)

“…This study uses 10 ELTeC corpora: English, French, German, Hungarian, Norwegian, Portuguese, Romanian, Serbian, Slovenian, and Spanish. ELTeC was created to reflect a sample of novels in various languages (the core collection consisting of 10, the expanded collection of 20 languages) from 1840 to 1920 based on criteria that ensured “rough comparability” ( Schöch et al , 2021 : 4) across subcollections. Each of the corpora includes 100 public-domain novels, with diverse metadata (author name, gender, publication date, word count, etc.)…”

“…canonicity, reflected in reprint count). Although the editors aimed at balanced subcollections and fair distribution according to variables, not all corpora could comply with the proposed criteria (for detailed discussions of the selection criteria and the process of corpus-building, see Burnard et al , 2021 ; Herrmann et al , 2020 ; Schöch et al , 2021 ).…”

“… 3 For detailed discussions of the selection criteria for the ELTeC collection, see Burnard et al , 2021 ; Schöch et al , 2021 . …”

Linguistic analysis of fiction texts in the context of the frame theory

“…Studying this relationship helps not only to expand but also to redefine how concepts of frames build literary contexts. The discovery of how frame structures affect the semantics, structure, and intertextual connections in texts stimulates further enrichment of the analysis of linguistic devices that contribute to the creation of a specific atmosphere and impression on readers (Schöch et al, 2021).…”

Parallel Stylometric Document Embeddings with Deep Learning Based Language Models in Literary Authorship Attribution

“…In order to create representative sub-collections for the corresponding languages, the novels were selected to evenly represent (1) novels of various sizes: short (10-50,000 words), medium (50-100,000 words), and long (more than 100,000 words); (2) four 20-year time periods T1 [1840-1859], T2 [1860-1879], T3 [1880-1899], T4 ; (3) the number of reprints, as a measure of canonicity (novels known to wider audience and completely forgotten), and (4) female and male authors [32].…”