A Study of Social Media Reviews Effects on the Success of Crowdfunding Projects

Abstract

Crowdfunding has become one of the important channels of getting fund for many start-ups. But, the low success rate has been a critical issue. Therefore, how to increase the success rate of fundraising projects is one of the main concerns of all fundraising activities. This work aims to study the effect of sentiment of reviews for the success of crowdfunding projects. We will use data mining and text mining to analyze the collected data. Least absolute shrinkage and selection operator (LASSO) and back-propagation networks (BPN) based feature selection will be employed to find the important factors for the success of crowdfunding projects. Next, support vector machines (SVM) will be employed to evaluate the performance of selected factors set. Experiment results can help fundraisers to increase the success rate of crowdfunding projects.