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.
翻译:虽然COVID-19的长期影响尚未确定,但其对人群筹资的直接影响仍然很大。本研究采取了一种计算方法,以更深入地理解这一变化。我们利用过去两年在GoFundMe上公布的所有运动的独特数据集,探索导致为人群筹资项目成功供资的各种因素。特别是,我们研究一组人群筹资项目,分析人群筹资网站通常存在的覆盖图像和其他变量。此外,我们建立了一个分类和回归模型,以评估基于 XGBoost 的特征的重要性。此外,我们采用反事实分析来调查人群筹资特征和成功之间的因果关系。更重要的是,我们进行了情绪分析和配对抽样测试,以审查2020年3月COVID-19爆发前后人群筹资运动的差异。首先,我们注意到在人群筹资成功方面存在着严重的种族差异。第二,我们发现通过运动描述表达的悲伤情绪在COVID-19爆发之后变得十分严重。考虑到所有这些因素,我们发现COVID-19对人群筹资运动的影响。