How does Japanese Sentiment Analysis work?
- Lexicon-based Analysis. This method uses predefined lists of words with associated sentiments to evaluate the overall sentiment of the text.
- Machine Learning. Machine learning models are trained on annotated datasets to classify the sentiment of unseen Japanese texts based on learned patterns.
- Natural Language Processing (NLP). NLP techniques are employed to preprocess and analyze text, extracting meaningful patterns and sentiment indicators.
- Deep Learning. Deep learning approaches such as neural networks are utilized to capture complex patterns in sentiment analysis, achieving higher accuracy.