Detecting Company-Specific Purchase Evidence from Twitter Posts

Delphia’s business model revolves around generating insights for investing firms that allow them to make better trading decisions. It has been shown that detecting when Twitter users post about recent or future purchases has the potential to increase the accuracy of company sales forecasts, which in turn can inform stock trading strategies. This internship project aims to develop automated means to detect and quantify purchase related posts on Twitter. The intern will conduct a machine learning project which will involve creating a dataset of purchase related tweets and using it to train a purchase tweet detector. Success in this project could lead to new data products for Delphia to sell to its financial investor clients.

Intern: 
So Hyun Park
Faculty Supervisor: 
Yang Xu
Province: 
Ontario
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