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[working paper]

dc.contributor.authorHoltdirk, Tobiasde
dc.contributor.authorSaju, Lorrainede
dc.contributor.authorFröhling, Leonde
dc.contributor.authorWagner, Claudiade
dc.date.accessioned2025-04-09T08:07:20Z
dc.date.available2025-04-09T08:07:20Z
dc.date.issued2025de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/101393
dc.description.abstractIn this guide, we give an overview of different large language models (LLMs) and their uses for research in the social and behavioral sciences. This guide does not only introduce essential concepts necessary to understand and think about this promising new type of resource but also serves as a practical guide for navigating the ever-changing landscape of available models and supports researchers in picking the best option for their needs. To account for some of the challenges and risks associated with the use of LLMs, this guide features discussions of issues like replicability, transparency, and generalizability.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherlarge language models, LLMs; generative language models; machine learning; model performance; benchmarkingde
dc.titleOverview of Large Language Models for Social and Behavioral Scientistsde
dc.description.reviewbegutachtetde
dc.description.reviewrevieweden
dc.source.volume16de
dc.publisher.countryDEUde
dc.publisher.cityKölnde
dc.source.seriesGESIS Guides to Digital Behavioral Data
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.identifier.urnurn:nbn:de:0168-ssoar-101393-6
dc.rights.licenceCreative Commons - Namensnennung, Nicht-kommerz. 4.0de
dc.rights.licenceCreative Commons - Attribution-NonCommercial 4.0en
ssoar.contributor.institutionGESISde
internal.statusformal und inhaltlich fertig erschlossende
dc.type.stockmonographde
dc.type.documentArbeitspapierde
dc.type.documentworking paperen
dc.source.pageinfo21de
internal.identifier.classoz10105
internal.identifier.document3
dc.contributor.corporateeditorGESIS - Leibniz-Institut für Sozialwissenschaften
internal.identifier.corporateeditor133
internal.identifier.ddc300
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence32
internal.identifier.pubstatus1
internal.identifier.review2
internal.identifier.series2387
ssoar.wgl.collectiontruede
internal.embargo.liftdate9999-01-01
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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