AI Sentiment Analysis for Stock Price Prediction

The patent combines sentiment analysis from social media sources with traditional transaction data into a unified prediction system. The sentiment analysis module processes user comments, opinions, and predictions from multiple social media platforms, then integrates this processed sentiment information with transaction data from financial institutions to generate stock price predictions, thereby improving prediction accuracy while managing system complexity through modular integration

The patent introduces an intermediary sentiment analysis module that acts as a bridge between raw social media data and the prediction engine. This intermediary component processes and structures unstructured sentiment data into usable features, then combines them with structured transaction data, serving as a mediator that enables accurate predictions without directly complicating the core prediction algorithm

The patent implements preliminary action by pre-processing and structuring sentiment data from multiple social media sources before the actual prediction is needed. The sentiment analysis module continuously monitors and processes user comments, opinions, and predictions, maintaining a ready-to-use sentiment database that can be quickly integrated with transaction data when predictions are required, thereby reducing real-time processing time while maintaining comprehensive data analysis

The patent segments the data processing into distinct modular components: a sentiment analysis module that handles social media data, a transaction data module that processes financial institution data, and a prediction engine that combines them. This segmentation allows each module to process its specific data type independently and efficiently, then integrate results without creating bottlenecks, thus improving prediction accuracy through comprehensive data integration while minimizing overall processing time