Monetizing entrepreneur response to crowdfunding with text analytics

Abstract

This paper examines the role of response in crowdfunding to guide fundraisers to monetize their responses better. In all, 6,405 commenters on a large crowdfunding platform in China (Modian.com) are observed. Grounded on the interaction texts, we identify, summarize, and extract the comments and the strategies for fundraisers to respond through several rounds of coding. It is found that potential investors comment to collect information or to express themselves, while fundraisers are either project-oriented or investor-oriented when responding to online reviews. We adopt the Naïve Bayes classifier to classify the crowdfunding demand of commenters, and entrepreneur's response strategy, as being either investor-oriented (60.8 %) or project-oriented (39.2 %). Econometric models are constructed to empirically test and quantify the impact of fundraiser response strategies on commenter investment decisions. The findings inform that commenters who are responded to by fundraisers are about 4 times more likely to invest than those who receive no response or receive responses from peer commenters. Also, a fundraiser project-oriented response strategy achieves 2.25 times better crowdfunding performance over an investor-oriented one. Robustness testing is performed using other criteria for classifying response strategies, as well as testing with a sample from another platform.