How does Sundanese Sentiment Analysis work?
- Tokenization. Tokenization breaks down text into individual words or phrases, making it easier to analyze sentiment.
- Sentiment Classification. Sentiment classification involves categorizing text as positive, negative, or neutral based on the language used.
- Feature Extraction. Feature extraction identifies key features from the text data to enhance the accuracy of sentiment analysis.
- Machine Learning Algorithms. Machine learning algorithms are used to train models that can predict sentiment based on learned patterns from the data.