anilguven/bert_tr_turkish_movie_reviews

Model Info

This model was developed/finetuned for movie review task for the Turkish Language. This model was finetuned via the Turkish movie review dataset.

• LABEL_0: positive review
• LABEL_1: negative review

Model Sources

• Dataset: http://humirapps.cs.hacettepe.edu.tr/tsad.aspx
• Paper: https://dl.acm.org/doi/10.1145/3557892
• Demo-Coding [optional]: https://github.com/anil1055/Turkish_Sentiment_Analysis-Hotel-and-Movie-Reviews/tree/main
• Finetuned from model [optional]: https://huggingface.co/dbmdz/bert-base-turkish-uncased

Preprocessing

You must apply removing stopwords, stemming, or lemmatization process for Turkish.

Results

• auprc = 0.9547155589592419
• auroc = 0.9567033960358541
• eval_loss = 0.4520341001172079
• fn = 1368
• fp = 1668
• mcc = 0.7727794159832003
• tn = 11682
• tp = 11982
• Accuracy: %92.11

Citation

BibTeX:

@article{10.1145/3557892, author = {Guven, Zekeriya Anil}, title = {The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment Analysis}, year = {2022}, issue_date = {February 2023}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {22}, number = {2}, issn = {2375-4699}, url = {https://doi.org/10.1145/3557892}, doi = {10.1145/3557892}, journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.}, month = {dec}, articleno = {55}, numpages = {16}, keywords = {Language model, sentiment analysis, social network, natural language processing, text classification, data analysis} }

APA:

Guven, Z. A. (2022). The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment Analysis. ACM Transactions on Asian and Low-Resource Language Information Processing, 22(2), 1-16.