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2023-06-07Zeitschriftenartikel DOI: 10.18452/27020
Machine learning for the history of ideas
dc.contributor.authorBrausch, Simon
dc.contributor.authorGraßhoff, Gerd
dc.date.accessioned2023-07-25T14:36:32Z
dc.date.available2023-07-25T14:36:32Z
dc.date.issued2023-06-07none
dc.date.updated2023-07-11T22:47:21Z
dc.identifier.issn2770-2030
dc.identifier.issn2770-2030
dc.identifier.urihttp://edoc.hu-berlin.de/18452/27712
dc.description.abstractThe information technological progress that has been achieved over the last decades has also given the humanities the opportunity to expand their methodological toolbox. This paper explores how recent advancements in natural language processing may be used for research in the history of ideas so as to overcome traditional scholarship's inevitably selective approach to historical sources. By employing two machine learning techniques whose potential for the analysis of conceptual continuities and innovations has never been considered before, we aim to determine the extent to which they can enhance conventional research methods. It will amount to a critical evaluation of how the advantages of computational in-breadth analysis could be combined with the merits of traditional in-depth analysis in a philosophically fruitful way. After a brief technical description, the approach will be applied to an example: the conceptual (dis)continuity between medieval and early modern philosophy. All the challenges encountered during development and application will be carefully evaluated. We will then be able to assess whether these tools and techniques present promising extensions to the methodological toolbox of traditional scholarship, or whether they do not yet have the potential for a task as complex as the analysis of philosophical literature. The present investigation can thus be seen as an experiment on how far one can go with current machine-learning techniques in this area of research. In doing so, it provides important insights and guidance for future advances in the field.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcomputational philosophyeng
dc.subjectdigital humanitieseng
dc.subjecthistory of ideaseng
dc.subjectmachine learningeng
dc.subjectnatural language processingeng
dc.subject.ddc004 Informatiknone
dc.subject.ddc100 Philosophie, Parapsychologie und Okkultismus, Psychologienone
dc.titleMachine learning for the history of ideasnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/27712-5
dc.identifier.doihttp://dx.doi.org/10.18452/27020
dc.type.versionpublishedVersionnone
local.edoc.pages22none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
dc.description.versionPeer Reviewednone
dcterms.bibliographicCitation.doi10.1002/fhu2.6none
dcterms.bibliographicCitation.journaltitleFuture humanitiesnone
dcterms.bibliographicCitation.volume1none
dcterms.bibliographicCitation.issue1none
dcterms.bibliographicCitation.articlenumbere6none
dcterms.bibliographicCitation.originalpublishernameWileynone
bua.departmentPhilosophische Fakultätnone

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