Review Dataset

Review datasets are crucial for training and evaluating sentiment analysis models, particularly in applications like movie reviews and product feedback. Current research focuses on improving model accuracy and explainability, employing techniques like multi-head attention mechanisms in transformers, multi-LLM negotiation frameworks, and explainable AI (XAI) algorithms such as SIDU-TXT to enhance interpretability. These advancements aim to address limitations of existing methods, such as generating generic or factually inaccurate explanations, and ultimately lead to more reliable and insightful sentiment analysis across diverse domains. The development and refinement of these datasets and associated models are vital for advancing natural language processing and improving user experiences in various online platforms.