How does Hebrew Sentiment Analysis work?
- Machine Learning. Various machine learning algorithms are trained on annotated Hebrew texts to classify documents' sentiments based on patterns in the data.
- Natural Language Processing. NLP techniques are utilized to preprocess Hebrew text, enabling the extraction of sentiment cues such as keywords, phrases, and context.
- Lexicon-based Analysis. This method employs predefined lists of words with assigned sentiment values to analyze texts and infer their overall sentiment.
- Deep Learning. Advanced deep learning models, such as neural networks, are used for more nuanced sentiment analysis by capturing complex patterns in Hebrew language data.