The Consequences of Authenticity: Quantifying Racial Signals and their Effects on Crowdfunding Success
54 Pages Posted: 11 Sep 2016 Last revised: 31 Jul 2018
Date Written: July 23, 2018
Crowdfunding platforms advise fundraisers to be authentic to gain trust from potential contributors; however, the campaign elements that project authenticity also introduce signals of racial identity that cause outcome disparities for fundraisers of color. This study uses a novel big-data methodology including facial recognition software, text analytics techniques, and econometrics to analyze the racial identifiers in the fundraiser photos, campaign photos, and project descriptions of more than 100,000 Kickstarter.com campaigns. It is unclear from prior literature which campaign elements actually affect success rates, whether Asian and black fundraisers face similar bias, and what is the best way to mitigate racial disparities in success rates.
Our findings show that the fundraiser photo and campaign photo both affect success rates, although the effect varies for Asian and black fundraisers. We also find that textual signals of race, such as “african” or “asian”, have a consistently strong effect on project outcomes. Partially because of these textual signals, there is a limit to how much using a ``generic” profile picture can improve the success rates for black fundraisers. Finally, we find that platforms can improve success rates for black and Asian fundraisers by signaling project quality, but that racial disparities still persist.
Keywords: crowdfunding, big data, diversity, economics, text mining, matched sample, empirical analysis
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