Effects of Extended Features on BERT Performance: Depression Detection

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dc.contributor.authorBalci, Emirhan
dc.contributor.authorSarac, Esra
dc.date.accessioned2026-02-27T07:33:28Z
dc.date.available2026-02-27T07:33:28Z
dc.date.issued2025
dc.description33rd Conference on Signal Processing and Communications Applications-SIU-Annual
dc.description.abstractIn this study, the effects of categorical and numerical additional features obtained from Twitter posts on depression detection were investigated. Depression detection performances of the BERT large language model and SVM classifier were compared on the dataset balanced with the oversampling method. The effects of two different feature addition methods, Unimodal and Concat, were evaluated on the BERT model. The results show that oversampling improves the performance of the BERT classifier, but feature addition methods do not provide significant improvement in the model performance. The findings of the experiments reveal the success of the BERT model in the field of classification and that it does not require additional features for the detection of depression. It is believed that this study will guide research in the field of depression detection and help researchers identify more effective areas of study.
dc.identifier.doi10.1109/SIU66497.2025.11112183
dc.identifier.isbn979-8-3315-6656-2; 979-8-3315-6655-5
dc.identifier.issn2165-0608
dc.identifier.urihttp://dx.doi.org/10.1109/SIU66497.2025.11112183
dc.identifier.urihttps://hdl.handle.net/20.500.14669/4594
dc.identifier.wosWOS:001575462500234
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2025 33rd Signal Processing and Communications Applications Conference, Siu
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20260302
dc.subjectdepression detection
dc.subjecttext classification
dc.subjectBERT
dc.subjectadditional feature addition
dc.titleEffects of Extended Features on BERT Performance: Depression Detection
dc.typeProceedings Paper

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