Our Research

We are a research team at University of Illinois at Urbana-Champaign, Computer Science Department, and our research focuses on crowdfunding issues. We focus on two research directions. Firstly, we evaluate current crowdfunding platforms and propose some suggestions to help creators improve their crowdfunding campaigns. Secondly, we are designing a new crowdfunding system that could increase the overall project success rate and encourage donors to donate based on project quality. We are looking forward to applying our research finding in real world to actually help people.


University of Illinois at Urbana-Champaign

Crowdfunding Research

Latest Research

CSCW 2017 : The Art and Science of Persuasion: Not All Crowdfunding Campaign Videos Are Same


It is important for a campaign to communicate ideas or products effectively to the potential backers. One of the lesser explored but powerful components of a crowdfunding campaign is the campaign video. To better understand how videos affect campaign outcomes, we analyzed videos from 210 Kickstarter campaigns across three different project categories. In a mixed-methods study,  we asked 3150 Amazon Mechanical Turk (MTurk) workers to evaluate the campaign videos. We found six recurrent factors from a qualitative analysis as well as quantitative analysis. Analysis revealed product related and video related factors that were predictive of the final outcome of campaigns over and above the static project representation features identified in previous studies.


SBP 2016 : Improving Donation Distribution for Crowdfunding : An Agent-Based Model

Donation-based crowdfunding has the potential to democratize capital raising by soliciting donations directly from the public through the Web and social media. These crowdfunding platforms, however, often function as unregulated open markets, in which there is minimal intervention to influence donation distribution across projects. In this paper, we propose a new donation distributing system that aim to (a) distribute donations more effectively among the projects, and (b) align the allocation of donations with the preferences of donors. An agent-based model was developed to test the proposed system. Results showed that the proposed system not only increased the overall success rates of projects, but also led to more successes for projects preferred by donors.