Diagnosing Core Topics in Digital Transformation Studies via Topic Model Approach

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Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi
Sayı: 57
Diagnosing Core Topics in Digital Transformation Studies via Topic Model Approach

Diagnosing Core Topics in Digital Transformation Studies via Topic Model Approach

Authors : Hüseyin Parmaksız, Osman Akarsu

Pages : 32-54

Doi:10.52642/susbed.1617370

View : 481 | Download : 121

Publication Date : 2025-08-30

Article Type : Research Paper

Abstract :The field of digital transformation continues to develop and expand rapidly due to technological advances. This study uses text mining techniques to analyze 5280 articles published between 2014 and 2024 using the LDA model and the Gibbs sampling method, the study identifies the most prominent topics on digital transformation research. Traditional methods, which rely on predefined categories and subjective judgment, are inadequate for identifying underlying themes in large datasets. The study identifies the most prominent topics in digital transformation research and tracks trends by tracking changes in topic rankings across different periods. It also explores sub- specialization areas across 1065 digital transformation journals and assesses how shifts in these areas impact the broader topic landscape. The findings provide valuable insights for practitioners, researchers, journal editors, and policymakers involved in digital transformation.
Keywords : Dijital Dönüşüm Araştırması, Metin Madenciliği, Topik Model Yaklaşımı

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