How does Korean Sentiment Analysis work?
- Tokenization. Tokenization breaks down text into individual words or phrases to analyze sentiment at a granular level.
- Sentiment Classification. Sentiment classification assigns predefined sentiment labels (positive, negative, neutral) to text based on the words used.
- Lexicon-Based Approaches. These approaches use predefined lists of words and their associated sentiments to determine the overall sentiment of the text.
- Machine Learning. Machine learning models are trained on labeled sentiment data to learn patterns and classify sentiments in new, unseen text.
