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Predicting Startup Success Using Publicly Available Data, Emily Gavrilenko
Predicting Startup Success Using Publicly Available Data, Emily Gavrilenko
Master's Theses
Predicting the success of an early-stage startup has always been a major effort for investors and venture funds. Statistically, there are about 305 million total startups created in a year, but less than 10% of them succeed to become profitable businesses. Accurately identifying the signs of startup growth is the work of countless investors, and in recent years, research has turned to machine learning in hopes of improving the accuracy and speed of startup success prediction.
To learn about a startup, investors have to navigate many different internet sources and often rely on personal intuition to determine the startup’s potential …