Predicting Equity Crowdfunding Success

Abstract

Equity crowdfunding has grown exponentially in the United States since the passage of the JOBS Act in 2013, yet it continues to be a research area that is relatively unexplored in the United States due to the limited availability of data. U.S equity crowdfunding campaigns are notoriously unsuccessful, and this paper develops a predictive model for equity crowdfunding success to determine whether the positivity of the language used, and the length of the campaign description influences an investor’s decision to invest. A model is developed on a balanced training set and applied to a test set, and the overall results are evaluated using a confusion matrix to determine the accuracy, precision, and recall of the model. Our overall results indicate that both the tone of sentiment and the length of the campaign description are predictive of an equity crowdfunding campaign’s success. Specifically, the potential investors appear to be attracted to positive campaign descriptions that are written with concise language.