Reward Styles-Sentiment Analysis Project

Sponsored by: rewardStyle Inc

 

Abstract
For this project, we analyze posts on social media platforms such as Twitter to determine if a post is positive or negative. Using data sentiment analysis, this web-based system flags any likely-abusive posts for human review if the post makes personal attacks, incites violence, uses abusive language, and/or generally makes the internet a worse place for others. Community Benefit: Our project is beneficial to both businesses and social media users. It allows companies to better observe user sentiment on their platforms and it helps to make social media platforms safer for social media users by flagging abusive posts.

Team Members

Muhammad Ahmed
Joshua Cidoni-Walker
Ali Fatta
Ali Khan
Ryan Wahler