Survey of Methods in Computational Literary Studies

=CLS INFRA D3.2: Series of five short survey papers on methodological issues


Christof Schöch, Julia Dudar, Evegniia Fileva


May 5, 2023 (v1.1.0)


Front Matter


Overview in grid shape General Introduction What is Authorship Attribution? What is Genre Analysis? What is Literary History? What is Gender Analysis? What is Canonicity? Introduction to Corpus Building Corpus Building for Authorship Attribution Corpus Building for Genre Analysis Corpus Building for Literary History Corpus Building for Gender Analysis Corpus Building for Canonicity


The aim of this publication is to document and describe current, widespread research practices in Computational Literary Studies (CLS), based on a large collection of publications that have been published in this field over the last approximately ten years. The perspective of this survey is primarily descriptive: it aims to document current, widespread practices as the authors were able to observe them in the published literature. In this sense, the survey, while far from exhaustive, can also serve as an annotated bibliography of sorts and as a guide to further reading. Despite the fact that this survey is not intended as an introductory textbook, it can nevertheless also serve as an introduction to several research areas and issues that are prominent within CLS as well as to several key methodological concerns that are of importance when performing research in CLS.

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Funding acknowledgement

This survey of research practices in Computational Literary Studies was prepared by a group of contributors in the framework of the Starting Community Computational Literary Studies Infrastructure (CLS INFRA) funded by the European Commission in the Horizon 2020 programme under Grant agreement ID 101004984.

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Christof Schöch, Julia Dudar, Evegniia Fileva, eds. (2023). Survey of Methods in Computational Literary Studies (= CLS INFRA D3.2: Series of Five Short Survey Papers on Methodological Issues). With contributions by Joanna Byszuk, Julia Dudar, Evegniia Fileva, Andressa Gomide, Lisanne van Rossum, Christof Schöch, Artjoms Šeļa and Karina van Dalen-Oskam. Version 1.1.0, May 5, 2023. Trier: CLS INFRA. URL:, DOI: 10.5281/zenodo.7892112.

License: Creative Commons Attribution 4.0 International (CC BY).