Summary
During the senior year of my undergraduate studies, I led a team of 3 students where we developed an analytical tool that suggests an online social media platform (Facebook or Twitter) to users to post content about a topic with the objective to maximize the reachability of the post at a given time.
The tool leverages Facebook API and Twitter API to extract real-time posts for a topic entered by the user. The tool then compares features such as number of likes, comments and shares in the posts retrieved from the online social media platforms.
We implemented Natural Language ToolKit (NLTK) library in the tool that processes extracted posts and suggests top keywords to grab attention of the readers.
We also implemented Logistics Regression (75% accuracy) and kNN Regression (82% accuracy) algorithms for the tool to predict which social media platform is ideal to post for a topic at a given time
We published a research paper under the same title.