How does Yiddish Sentiment Analysis work?
- Text Preprocessing. This method involves cleaning and preparing Yiddish text for analysis by removing noise, normalizing words, and segmenting sentences.
- Sentiment Classification. This technique categorizes Yiddish texts into defined sentiment classes (positive, negative, neutral) using machine learning algorithms.
- Lexicon-Based Approaches. Lexicon-based methods utilize predefined sentiment lexicons containing Yiddish words and phrases associated with specific sentiments for analysis.
- Deep Learning Models. Advanced deep learning models such as recurrent neural networks (RNNs) are used to capture the contextual meaning and sentiment in Yiddish texts.