Development of a Sentiment Analysis and Text Mining System

Data Science — 2025, Undergraduate

This study developed a sentiment analysis and text mining system that classifies customer reviews and extracts frequent terms, entities, and theme scores. Users upload text or connect to review exports and inspect visual summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and NLTK. The findings showed that the system provided fast and consistent opinion insights, while achieving a high System Usability Scale score. The study recommends use in customer feedback and brand monitoring units.

Homepage screenshot

Report a problem with this project