incidelen/bert-base-multilingual-turkish-sentiment-analysis-cased

🇹🇷 BERTurk for Turkish Sentiment Analysis

This model is a fine-tuned version of mBERT on the TRSAv1 dataset, a labeled collection of Turkish e-commerce reviews categorized into positive, neutral, and negative sentiments. For more details about the dataset, methodology, and experiments, you can refer to the corresponding research paper.

How to Use

You can use the model directly with 🤗 Transformers:

from transformers import pipeline

classifier = pipeline("text-classification", model="incidelen/bert-base-multilingual-turkish-sentiment-analysis-cased")
result = classifier("Ürün çok kaliteli, paketleme harikaydı. Kesinlikle tavsiye ederim!")
print(result)

Citation

If you use this model in your research or application, please cite the following paper:

@article{incidelen15sentiment,
  title={Sentiment Analysis in Turkish Using Language Models: A Comparative Study},
  author={{\.I}ncidelen, Mert and Aydo{\u{g}}an, Murat},
  journal={European Journal of Technique (EJT)},
  volume={15},
  number={1},
  pages={68--74},
  publisher={Hibetullah KILI{\c{C}}}
}

Dataset Overview

The TRSAv1 dataset includes 150,000 Turkish product reviews from e-commerce platforms. It is balanced across three sentiment classes:

Evaluation Results

Overall Performance

Class-wise Performance

Acknowledgments

Special thanks to maydogan for their contributions and support.