Britain's mood, entailed weekly: In silico longitudinal surveys with fine-tuned Large Language Models

DOI:	https://doi.org/10.1145/3630744.3659829
URL:	https://dl.acm.org/doi/10.1145/3630744.3659829
Document Type:	Conference or workshop publication
Year of publication:	2024
Book title:	WebSci Compaion '24 : Companion proceedings of the 16th ACM Web Science Conference 2024; reflecting on the web, AI and society
Page range:	47-50
Conference title:	WebSci '24
Location of the conference venue:	Stuttgart, Germany
Date of the conference:	21.-24.05.2024
Place of publication:	New York, NY
Publishing house:	ACM
ISBN:	979-8-4007-0453-6
Related URLs:	https://dl.acm.org/doi/pdf/10.1145/36307... https://dl.acm.org/doi/proceedings/10.11...
Publication language:	English
Institution:	Business School > Data Science in the Economic and Social Sciences (Strohmaier, 2022-)
Subject:	004 Computer science, internet

Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation.

BASE: Ahnert, Georg ; Pellert, Max ; Garcia, David ; Strohmaier, Markus

Google Scholar: Ahnert, Georg ; Pellert, Max ; Garcia, David ; Strohmaier, Markus

ORCID: Ahnert, Georg

; Pellert, Max

; Garcia, David

; Strohmaier, Markus

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