Boosting Sentiment Analysis with BERT for Low-Resource Languages

This research from ArXiv focuses on improving BERT fine-tuning for sentiment analysis, specifically addressing challenges in languages with limited data. The paper's contribution likely lies in novel techniques or adaptations to enhance performance in these lower-resourced settings.

• •Focuses on improving sentiment analysis in languages with limited data.
• •Utilizes BERT, a pre-trained language model, for fine-tuning.
• •Potentially introduces novel techniques for improved performance.