How does Swedish Sentiment Analysis work?
- Lexicon-Based Approach. This approach uses predefined lists of words associated with specific sentiments to analyze text and determine overall sentiment by scoring the presence of these words.
- Machine Learning. Machine learning models are trained on labeled datasets to recognize patterns and classify text as positive, negative, or neutral based on their learned features.
- Natural Language Processing (NLP). NLP techniques are applied to understand and interpret the nuances of language, including context and idiomatic expressions that convey sentiment.
- Deep Learning. Advanced neural networks, such as recurrent neural networks (RNNs), process large amounts of text data to identify complex sentiment patterns that simpler models may miss.
