Customer Complaint Classification with Large Language Models

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dc.contributor.authorGüllü, Merve
dc.contributor.authorAtagün, Ercan
dc.contributor.authorBiroǧul, Serdar
dc.contributor.authorBarişçi, Necaattin
dc.date.accessioned2026-07-01T11:36:27Z
dc.date.available2026-07-01T11:36:27Z
dc.date.issued2025
dc.departmentDüzce Üniversitesi
dc.description2nd International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025 -- 7 August 2025 through 9 August 2025 -- Antalya -- 213104
dc.description.abstractAutomatic classification of customer complaints is of great importance for companies to detect customer problems early, optimize service processes and increase customer satisfaction. Customer complaint data provided as textual data consists of very insightful information in terms of addressing the problems encountered. In this study, deep learning-based approaches (LSTM, CNN), transformer-based models (BERT, RoBERTa) and large language models (GPT-2, Llama3.1-8B) are compared using two customer complaint datasets with different class distributions. The results show that LLMs achieve higher accuracy and F1 scores in both training and test phases. In particular, the fine-tuning process applied to the large language models enabled them to be tailored to the problem and contributed to the higher performance of LLMs compared to other models. © 2025 IEEE.
dc.description.sponsorshipAntalya Bilim University; IEEE
dc.identifier.doi10.1109/ACDSA65407.2025.11166338
dc.identifier.isbn979-833153562-9
dc.identifier.scopus2-s2.0-105018466261
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ACDSA65407.2025.11166338
dc.identifier.urihttps://hdl.handle.net/20.500.12684/23037
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofInternational Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260623
dc.subjectBert
dc.subjectCustomer complaint
dc.subjectGPT
dc.subjectLlama
dc.subjectLLM
dc.subjectRoBERTa
dc.titleCustomer Complaint Classification with Large Language Models
dc.typeConference Object

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