Christof Schöch: “Repetitive Research: A Conceptual Space and Terminology of Replication, Reproduction, Re-Implementation, Re-Analysis, and Re-Use in Digital Humanities”, International Journal of Digital Humanities, 2023. – DOI: 10.1007/s42803-023-00073-y. 
Tamara Radak, Lou Burnard, Pieter Francois, Agnes Hilger, Fotis Jannidis, Gábor Palkó, Roxana Patras, Michael Preminger, Diana Santos, Christof Schöch: “Towards a Computational History of Modernism in European Literary History: Mapping the Inner Lives of Characters in the European Novel, 1840–1920”. Open Research Europe: Digital Humanities, 2023. – DOI: https://doi.org/10.12688/openreseurope.16290.1.
Nanette Rißler-Pipka; José Calvo Tello; Stefan E. Funk; Carolin Odebrecht; Christof Schöch; Ubbo Veentjer: “The European Literary Text Collection in TextGrid Repository” (poster). Digital Humanities Conference 2023: Collaboration as Opportunity (DH2023). Graz: ADHO, 2023. – DOI: https://doi.org/10.5281/zenodo.8093217.
Christof Schöch (2023): “Post-Scriptum”. In: Survey of Methods in Computational Literary Studies (= D 3.2: Series of Five Short Survey Papers on Methodological Issues). Edited by Christof Schöch, Julia Dudar, Evegniia Fileva. Trier: CLS INFRA. URL: https://methods.clsinfra.io/postscriptum.html – DOI: 10.5281/zenodo.7892112.
Christof Schöch (2023): “Annotation for Genre Analysis”. In: Survey of Methods in Computational Literary Studies (= D 3.2: Series of Five Short Survey Papers on Methodological Issues). Edited by Christof Schöch, Julia Dudar, Evegniia Fileva. Trier: CLS INFRA. URL: https://methods.clsinfra.io/annotation-genre.html, DOI: 10.5281/zenodo.7892112.
Christof Schöch (2023): “What is Genre Analysis?”. In: Survey of Methods in Computational Literary Studies (= D 3.2: Series of Five Short Survey Papers on Methodological Issues). Edited by Christof Schöch, Julia Dudar, Evegniia Fileva. Trier: CLS INFRA. URL: https://methods.clsinfra.io/what-genre.html, DOI: 10.5281/zenodo.7892112.
Andressa Gomide, Christof Schöch (2023): “Introduction to Data Analysis”. In: Survey of Methods in Computational Literary Studies (= D 3.2: Series of Five Short Survey Papers on Methodological Issues). Edited by Christof Schöch, Julia Dudar, Evegniia Fileva. Trier: CLS INFRA. URL: https://methods.clsinfra.io/analysis-intro.html, DOI: 10.5281/zenodo.7892112.
Christof Schöch (2023): “General Introduction”. In: Survey of Methods in Computational Literary Studies (= D 3.2: Series of Five Short Survey Papers on Methodological Issues). Edited by Christof Schöch, Julia Dudar, Evegniia Fileva. Trier: CLS INFRA. URL: https://methods.clsinfra.io/general-intro.html, DOI: 10.5281/zenodo.7892112.
Antonija Primorac, Rosario Arias, Pieter François, Roxana Patras, Eva Eglāja-Kristsone, Karina van Dalen-Oskam, Berenike Hermann, Christof Schöch: “Distant Reading Two Decades on: Reflections on the Digital Turn in the Study of Literature”. Digital Studies / Le Champ numérique, 2023. – DOI: https://doi.org/10.16995/dscn.8855.
Christof Schöch, Julia Dudar and Evgeniia Fileva, eds. (2023). Survey of Methods in Computational Literary Studies (=CLS INFRA D3.2). With contributions by Joanna Byszuk, Julia Dudar, Evegniia Fileva, Andressa Gomide, Lisanne van Rossum, Christof Schöch, Artjoms Šeļa and Karina van Dalen-Oskam. Trier: CLS INFRA. – URL: https://methods.clsinfra.io/ · DOI: 10.5281/zenodo.7782363.
Schöch, Christof (2023). “Quantitative Semantik: Word Embedding Models für literaturwissenschaftliche Fragestellungen”. In Digitale Literaturwissenschaft. Beiträge des DFG-Symposiums 2017, edited by Fotis Jannidis. Stuttgart: Metzler. – DOI: 10.1007/978-3-476-05886-7_22.
Christof Schöch (2023): “Review of: Nicholas D. Paige, Technologies of the Novel, 2021”. In: H-France Review 23(22). – URL: https://h-france.net/vol23reviews/vol23no22schoch.pdf. – See also: https://github.com/christofs/paige (repository).
Co-Editor, Journal of Computational Literary Studies, with Evelyn Gius and Peer Trilcke. Editorial team members: Élodie Ripoll, Svenja Guhr, Henny Sluyter-Gäthje, Dominik Gerstorfer. 2021-present. – https://jcls.io.