This study presents an expanded new dataset and a hybrid BERT-SVM model for fake news detection in Turkish. As part of the research, news articles collected from FCTR, SOSYALAN, X-Fact datasets and Turkish fact-checking platforms teyit.org, and dogrulukpayi.com were combined to create a comprehensive dataset containing more than 20 thousand news articles. To improve classification accuracy, a hybrid approach integrating a fine-tuned BERTurk model with Support Vector Machines (SVM) was proposed. Additionally, model predictions were evaluated in terms of stylistic bias. The results demonstrate that BERT-based hybrid models have significant potential in addressing the unique challenges of fake news detection in Turkish.