{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T15:49:56Z","timestamp":1777218596152,"version":"3.51.4"},"reference-count":98,"publisher":"Walter de Gruyter GmbH","issue":"4-5","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8,27]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p xml:lang=\"en\">In this article, we provide an overview of machine learning as it is applied in computational literary studies, the field of computational analysis of literary texts and literature related phenomena. We survey a number of scientific publications for the machine learning methodology the scholars used and explain concepts of machine learning and natural language processing while discussing our findings. We establish that besides transformer-based language models, researchers still make frequent use of more traditional, feature-based machine learning approaches; possible reasons for this are to be found in the challenging application of modern methods to the literature domain and in the more transparent nature of traditional approaches. We shed light on how machine learning-based approaches are integrated into a research process, which often proceeds primarily from the non-quantitative, interpretative approaches of non-digital literary studies. Finally, we conclude that the application of large language models in the computational literary studies domain may simplify the application of machine learning methodology going forward, if adequate approaches for the analysis of literary texts are found.<\/jats:p>","DOI":"10.1515\/itit-2023-0041","type":"journal-article","created":{"date-parts":[[2023,8,25]],"date-time":"2023-08-25T05:20:26Z","timestamp":1692940826000},"page":"200-217","source":"Crossref","is-referenced-by-count":9,"title":["Machine learning in computational literary studies"],"prefix":"10.1515","volume":"65","author":[{"given":"Hans Ole","family":"Hatzel","sequence":"first","affiliation":[{"name":"Department of Informatics , Universit\u00e4t Hamburg , Vogt-K\u00f6lln-Stra\u00dfe 30, 22527 Hamburg , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haimo","family":"Stiemer","sequence":"additional","affiliation":[{"name":"Technical University of Darmstadt, Institute of Linguistics and Literary Studies , Residenzschloss 1, 64283 Darmstadt , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chris","family":"Biemann","sequence":"additional","affiliation":[{"name":"Department of Informatics , Universit\u00e4t Hamburg , Vogt-K\u00f6lln-Stra\u00dfe 30, 22527 Hamburg , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evelyn","family":"Gius","sequence":"additional","affiliation":[{"name":"Technical University of Darmstadt, Institute of Linguistics and Literary Studies , Residenzschloss 1, 64283 Darmstadt , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2023,8,25]]},"reference":[{"key":"2023112113471176820_j_itit-2023-0041_ref_001","unstructured":"P. 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