Team Members: Ajay Patel, Francesco Colombo, Ruiyang Peng, Sen Liu, Yijie Bai
The Goergen Institute of Data Science and Artificial Intelligence (GIDS-AI) aims to discern whether the contents of Statements of Purpose (SOPs) submitted by its master’s in data science applicants can provide insights about applicants and indicate whether they will accept an admission offer to the program. Therefore, the goal of this project was to build a predictive model capable of forecasting an applicant’s decision by analyzing their SOP. To achieve this goal, students used emotion and sentiment analysis on SOPs to determine which sentiments applicants most commonly express. The team then passed these sentiments through predictive models, including logistic regression and random forest models, and incorporated admission and demographic traits to see if they held any relevance. While students were able to measure generally hopeful sentiments and achieved predictions that were better than a random baseline, their correlation analysis and results demonstrated that SOPs alone cannot be used to predict applicants’ admission acceptance decisions.