Analysis of Diplomatic Texts with LLMs: A Hybrid Approach in Computational Social Sciences

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dc.contributor.authorKurnaz, Ahmet
dc.contributor.authorUnver, Akin
dc.date.accessioned2026-02-03T12:00:44Z
dc.date.available2026-02-03T12:00:44Z
dc.date.issued2025
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description33rd Conference on Signal Processing and Communications Applications-SIU-Annual -- JUN 25-28, 2025 -- Istanbul, TURKIYE
dc.description.abstractThis paper presents the practical application of big language models in text mining and topic modeling processes using texts shared online by the Ministry of Foreign Affairs of the Republic of Turkiye. The research describes an iterative and hybrid algorithm in which domain experts and large language models work together. The findings indicate that well-defined themes play a critical role in model success. It is emphasized that in social sciences, topic modeling processes should be handled with a tailor-made approach that includes the contextual interpretations of the researcher in the data evaluation processes, rather than being evaluated only through numerical outputs. In conclusion, the proposed algorithm offers a comprehensive and flexible analysis opportunity in social scientific research by generating topic labels suitable for qualitative or quantitative analysis of texts.
dc.identifier.doi10.1109/SIU66497.2025.11112347
dc.identifier.isbn979-8-3315-6656-2
dc.identifier.isbn979-8-3315-6655-5
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-105015463350
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/SIU66497.2025.11112347
dc.identifier.urihttps://hdl.handle.net/20.500.12428/34689
dc.identifier.wosWOS:001575462500317
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIeee
dc.relation.ispartof2025 33rd Signal Processing and Communications Applications Conference, Siu
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20260130
dc.subjecttopic modelling
dc.subjectLLMs
dc.subjectnatural language processing
dc.titleAnalysis of Diplomatic Texts with LLMs: A Hybrid Approach in Computational Social Sciences
dc.typeConference Object

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