How does Chichewa Sentiment Analysis work?
- Tokenization. Tokenization involves breaking down Chichewa text into individual words or phrases, which helps in analyzing the sentiment conveyed in each part of the text.
- Sentiment Classification. This method categorizes the tokens into predefined sentiment labels (positive, negative, neutral) using machine learning algorithms trained on Chichewa language data.
- Lexicon-based Approach. In a lexicon-based approach, a predefined list of Chichewa words with assigned sentiment scores is used to evaluate the overall sentiment of the text.
- Machine Learning Models. Various machine learning models, including support vector machines and neural networks, are employed to learn from annotated Chichewa datasets to improve sentiment analysis accuracy.
