Smith Brain Trust / March 20, 2018

Overcome Crowdfunding Discrimination

Overcome Crowdfunding Discrimination

Women Leading Research: Jessica M. Clark

SMITH BRAIN TRUST – People looking to raise money using crowdfunding sites are encouraged to be authentic in their profiles and project descriptions. It’s the best way, they’re told, to connect with potential donors and engender trust. But what about when it’s not?

Research from Jessica M. Clark, assistant professor of Decisions, Operations and Information Technologies at the University Of Maryland’s Robert H. Smith School of Business, finds that for some fundraisers, being authentic – particularly when it comes to race – can actually stand in the way of their fundraising goals. The researchers studied the ways that fundraisers signal racial identity on Kickstarter, the effects of those signals on their success, and the cost of being authentic.

Clark’s co-author, Wake Forest University’s Lauren Rhue, collected images from Kickstarter, both from project description pages and profile pages, and used classification software to determine which races were represented. She later broadened the study to include signals about race included in the project text. That’s when Clark joined the research.

“We decided that maybe you could tell the race of a person just based on the words they use in their project description,” Clark says.

The researchers discovered that while the fundraiser’s visually perceived race had the most meaningful impact on the probability of success, the racial components in the text also carried significant weight. In their working paper, they include a table of words that are found to be highly correlated with race.

Some are unsurprising, Clark says. Words such as “Africa,” are disproportionately used by black fundraisers to describe their projects, as are some cultural words, such as “jazz” or “hip-hop.”

“When I’m talking about this research at conferences, I ask people if they remember the old  blog ‘Stuff White People Like.’ A lot of the words that white people use in their project descriptions happen to be stuff that showed up on that blog,” she says. The words “Oregon,” “coffee,” and “rock and roll” were a few.

The researchers also found differences in the way white and black fundraisers talk about similar projects involving black subjects. Black fundraisers, she said, more frequently referred to such projects using cultural terms, like “jazz” and “hip-hop,” and more often used words like “community,” “God” and “youth.” White fundraisers, meanwhile, tend to talk about projects involving black subjects using terms that are more altruistic in tone, such as “hope,” “charity” and “help.”

Overall, they found that white fundraisers had greater success than black fundraisers, and that Asian fundraisers had higher success rates than any other group. “It’s the ‘model minority’ concept,” Clark says. “We think that Asian fundraisers benefit from that phenomenon – that they are stereotyped as being smarter, working harder, and doing all the right things to attain success.”

The research carries broad implications, not just for fundraisers and their endeavors, but also for the fundraising sites that stand to benefit from their projects.

“A common recommendation when faced with racial bias online is simply to remove all racial signals from your posting – whether it’s an Airbnb accommodations posting, or your Craigslist posting or your Kickstarter project,” Clark says.

While it’s fairly simple to replace the fundraiser’s photo with a generic image, when it comes to presenting a project description, Clark says, “it’s almost impossible” to remove racial indicators completely from the text and visual portions of a project description. “These common recommendations,” she says, “are just not very actionable.”

In cases where all all racial signals are stripped from photographs and text, the posting can become strikingly vague. And that leads to other problems.

“Then you’re not just vague, but untrustworthy. We include these visual elements as a measure of trust. You’re saying, ‘This is me. This is who I am. You should trust me.’ If you remove details from your project, you remove specifics, which is something that people want to see,” says Clark.

So, she adds, minority fundraisers are faced with this dilemma: Do I appear untrustworthy or vague, or do I reveal who I am and possibly risk seeing lower success rates? 

Kickstarter should consider ways to mitigate  racial disparities among projects – for instance, providing fundraising training in minority communities or reaching out to individual fundraisers with tips that can improve their project pages, Clark says. 

In their research, Clark and Rhue found that racial disparities are almost non-existent among projects designated by Kickstarter as a “Projects We Love.” However, they also found that Kickstarter assigns this stamp of approval “very disproportionately” to projects from white and Asian fundraisers.

“The question then becomes: Is the responsibility for eliminating racial disparities on the project creators themselves or on a platform itself, like Kickstarter,” Clark says.  

She and Rhue considered that question, concluding that there’s only so much you can ask fundraisers to do, when almost any step they take to obscure racial signals can work against them. 

“If you really care about reducing racial bias,” she says, “you should take action. It will benefit you not only because it’s the right thing to do,  but also because it is financially beneficial.” 

If Kickstarter sees one group that is doing disproportionately poorly, helping that group perform better will only help Kickstarter in the long run, she says.

Further proof of that benefit, Clark says, is this fact: Black fundraisers are significantly more likely to bring in first-time donors – people who haven’t backed any other projects. “They are increasing the user base,” she says.

Jessica M. Clark is assistant professor of information systems at the University of Maryland's Robert H. Smith School of Business.

Research interests: Use of machine learning techniques and individual-level data to explore the relationship between demographic characteristics and behaviors, and how that relationship affects financial or social outcomes. Past work has included developing algorithms for disambiguating consumers’ use of a shared device (specifically, a television Set-Top Box); investigating the utility of highly fine-grained transactional data for predicting consumers’ responses to marketing offers at a bank; and evaluating the utility of commonly used statistical modeling techniques in the context of massive data sets. Her current interests focus on using analytics to better understand racial and gender dynamics on online platforms such as and

Selected accomplishments: A recent project, “Mining Massive Fine-Grained Behavior Data to Improve Predictive Analytics” (published in Management Information Systems Quarterly) was awarded the 2017 European Research Paper of the Year by the Association for Information Systems. She was also a member of a winning team at the first ever paper-a-thon at the International Conference on Information Systems in Seoul, Korea.

About this series: The Smith School faculty is celebrating Women’s History Month 2018 in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Daily faculty spotlights support activities from the school’s Office of Diversity Initiatives, starting with the seventh annual Women Leading Women forum on March 1, 2018.

Other fearless ideas from:  Rajshree Agarwal  |  Ritu Agarwal  |  T. Leigh Anenson  |  Kathryn M. Bartol  |  Christine Beckman  |  Margrét Bjarnadóttir  |  M. Cecilia Bustamante  |  Jessica M. Clark  |  Rellie Derfler-Rozin  |  Waverly Ding  |  Wedad J. Elmaghraby  |  Rosellina Ferraro  |  Rebecca Hann  | Amna Kirmani  |  Hanna Lee  |  Hui Liao  |  Jennifer Carson Marr  |  Wendy W. Moe  |  Courtney Paulson  |  Louiqa Raschid  |  Rebecca Ratner  |  Rachelle Sampson  |  Debra L. Shapiro  |  M. Susan Taylor  |  Niratcha (Grace) Tungtisanont  |  Vijaya Venkataramani  |  Janet Wagner  |  Yajin Wang  | Liu Yang  |  Jie Zhang  |  Lingling Zhang



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