Predictive Analytics through Sentiment Analysis

This whitepaper presents a case study that taps into the textual content of financial news articles/blogs at regular intervals of time, process it, store the features extracted into a database, build the model, and finally predict stock movement for a defined period ahead. The article is passed through a data processing pipeline which consists of multiple steps like Named Entity Extraction, Sentiment Analysis and a customized algorithm.