Title:

Social Media Sentiment Analysis

The main purpose of this project is to perform sentiment analysis about Fidelity’s virtual assistant and chat-bot products. This project’s value to Fidelity is based on how customers feel about these products. They should be able to tell how happy users are with their product as well as finding any deficiencies. This would determine if Fidelity will have to make changes to their product to satisfy customer needs. When the user visits the webpage dashboard, they should be able to understand the overall sentiment of their preferred social media platform within 5 minutes. A sentiment model is a machine learning algorithm used to determine if a certain text is positive or negative in tone, based on its context. High negative scores indicate that the text is negative in tone, while high positive scores indicate the opposite. There are multiple deliverables in this project. This includes multiple web crawlers, which scour the internet using public APIs to scrape data from Reddit and the Google Play Store. The sentiment analysis is performed by using machine learning models & NLTK. Results are stored inside a database, which also provides endpoints for access by external sources.

Name

Comment*

Comments are viewable only by submitter

Captcha*