SAĞLIK YÖNETİMİNDE TEZLERİN KONU DAĞILIMI VE TREND ANALİZİ: BERTopic YAKLAŞIMIYLA BİR İNCELEME
Sağlık Yönetiminde Tezlerin Konu Dağılımı ve Trend Analizi
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Sağlık Yönetimi, BERTopic, Doğal Dil İşleme, Konu ModellemeÖzet
Bu çalışmanın temel amacı, sağlık yönetimi alanındaki tez verilerini, veri madenciliği ve doğal dil işleme tekniklerinden biri olan BERTopic algoritması aracılığıyla incelemektir. Yükseköğretim Kurulu Tez Merkezi veri tabanından elde edilen 6514 tez, metin temizleme, kelime tokenizasyonu, stopword temizleme, lemmatization ve TF-IDF ağırlıklama gibi doğal dil işleme teknikleri kullanılarak işlenmiştir. Daha sonra, Transformer tabanlı BERTopic modeli kullanılarak tezlerin konu dağılımı ve tematik yapıları analiz edilmiştir. Analiz sonuçları, yüksek lisans tezlerinin üretimde baskın olduğunu, üniversiteler arasında tez üretiminde belirgin farklılıklar bulunduğunu ve farklı büyüklüklere sahip 10 (on) ana konu alanı belirlendiğini göstermiştir. Ayrıca, yıllara göre tez üretiminde 2019 yılına kadar istikrarlı bir artış olduğu, son beş yılda ise düşüş eğilimine geçtiği tespit edilmiştir. Çalışma, sağlık yönetimi alanındaki akademik üretimin tür ve konu açısından çeşitlilik gösterdiğini ortaya koymakta olup, elde edilen bulgular hem akademik politikaların hem de araştırma stratejilerinin şekillenmesinde yol gösterici niteliktedir.
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- 2025-10-26 (2)
- 2025-09-30 (1)
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Telif Hakkı (c) 2025 Göbeklitepe Sağlık Bilimleri Dergisi
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