Sentiment Score

Sentiment score analysis aims to quantify the emotional tone expressed in text, images, or other data, often serving as a crucial feature in various applications. Current research focuses on improving sentiment score accuracy and contextual understanding using deep learning models like BERT and transformers, exploring techniques such as aspect-based sentiment analysis and causal discovery to enhance precision and address biases. These advancements have significant implications for fields ranging from social media monitoring and financial market prediction to improving the quality of training data for other machine learning tasks.