Sentiment Aware

Sentiment analysis, the computational identification and classification of opinions expressed in text, is undergoing rapid advancement, driven by the application of large language models (LLMs) and deep learning architectures like BERT, BiLSTM, and GRU. Current research focuses on improving accuracy, particularly in nuanced contexts like financial markets and social media, addressing challenges such as handling multiple languages, fine-grained sentiment detection, and mitigating biases in model outputs. These improvements have significant implications for various fields, enabling more effective monitoring of public opinion, prediction of market trends, and the development of fairer and more robust AI systems.