Multilingual Sentiment

Multilingual sentiment analysis aims to automatically determine the emotional tone of text across multiple languages, a crucial task with applications ranging from social media monitoring to market research. Current research focuses on addressing biases in existing models, particularly towards high-resource languages, and improving performance in low-resource languages through techniques like ensemble methods, multilingual lexicons, and adapter-based transfer learning. These advancements are vital for creating more equitable and effective natural language processing systems capable of understanding diverse global perspectives and fostering cross-cultural communication.