Project Success Prediction in Crowdfunding Environments

Crowdfunding has gained widespread attention in recent years. Despite the huge success of crowdfunding platforms, the percentage of projects that succeed in achieving their desired goal amount is less than 50%. Moreover, many of these crowdfunding platforms follow “all-or-nothing” policy which means the pledged amount is collected only if the goal is reached within a certain predefined time duration. Hence, estimating the probability of success for a project is one of the most important research challenges in the crowdfunding domain. To predict the project success, there is a need for new prediction models that can potentially combine the power of both classification (which incorporate both successful and failed projects) and regression (for estimating the time for success). We propose a novel formulation for the project success prediction and develop a censored regression approach where one can perform regression in the presence of partial information. We rigorously evaluate th...

• Type: Journal
• Year: 2016
• Where: WSDM
• Authors: Yan Li, Vineeth Rakesh, Chandan K. Reddy
• Keywords: Data Mining, WSDM 2016