How does Uyghur Sentiment Analysis work?
- Sentiment Classification. This method categorizes text into predefined sentiment categories (positive, negative, neutral) based on the linguistic and contextual features of Uyghur language.
- Lexicon-Based Analysis. Uses pre-compiled lists of words with associated sentiment scores to evaluate the overall sentiment of content by aggregating the scores of individual words.
- Machine Learning Techniques. Involves training algorithms on labeled data to recognize patterns in sentiment, allowing the model to classify unseen Uyghur text for sentiment analysis.
- Deep Learning Models. Utilizes advanced neural networks, such as LSTM or BERT, to capture complex patterns and dependencies in Uyghur text for more nuanced sentiment understanding.