  While the long-term effects of COVID-19 are yet to be determined, its
immediate impact on crowdfunding is nonetheless significant. This study takes a
computational approach to more deeply comprehend this change. Using a unique
data set of all the campaigns published over the past two years on GoFundMe, we
explore the factors that have led to the successful funding of a crowdfunding
project. In particular, we study a corpus of crowdfunded projects, analyzing
cover images and other variables commonly present on crowdfunding sites.
Furthermore, we construct a classifier and a regression model to assess the
significance of features based on XGBoost. In addition, we employ
counterfactual analysis to investigate the causality between features and the
success of crowdfunding. More importantly, sentiment analysis and the paired
sample t-test are performed to examine the differences in crowdfunding
campaigns before and after the COVID-19 outbreak that started in March 2020.
First, we note that there is significant racial disparity in crowdfunding
success. Second, we find that sad emotion expressed through the campaign's
description became significant after the COVID-19 outbreak. Considering all
these factors, our findings shed light on the impact of COVID-19 on
crowdfunding campaigns.
