Negative Sentiment

Negative sentiment analysis focuses on identifying and understanding negative expressions in text and speech, aiming to quantify and contextualize negativity across various domains. Current research employs diverse machine learning models, including transformers and support vector machines, often incorporating techniques like sentiment lexicons and contextual embeddings to improve accuracy and address challenges like bias and the detection of subtle negativity. This research is crucial for applications ranging from social media monitoring and mental health support to financial market prediction and the mitigation of harmful online discourse, offering valuable insights into human behavior and communication patterns.