Unified Approach to Structured Sentiment Analysis

The Structured Sentiment Analysis project aims to develop a model to extract detailed sentiment information from text. Rather than just determining whether the sentiment of a text is positive or negative, this project goes a step further to identify the "Source" (who is expressing the sentiment), "Target" (what the sentiment is about), "Polar_expression" (the specific words or phrases describing the sentiment), and "Polarity" (the overall sentiment value). This involves processing complex natural language data and training a model to capture these sentiment elements accurately. The project utilizes state-of-the-art transformer models for the sentiment analysis task. The goal is to create a robust system that can handle real-world text data and provide detailed sentiment analysis that can be valuable for various applications, such as customer feedback analysis, social media monitoring, and market research.