Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

4-2014

Abstract

To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for project failure is the inability of founders to connect with a sufficient number of investors, and that is mainly because hitherto there has not been any automatic way of matching creators and investors. We thus set out to propose different ways of recommending investors found on Twitter for specific Kickstarter projects. We do so by conducting hypothesis-driven analyses of pledging behavior and translate the corresponding findings into different recommendation strategies. The best strategy achieves, on average, 84% of accuracy in predicting a list of potential investors' Twitter accounts for any given project. Our findings also produced key insights about the whys and wherefores of investors deciding to support innovative efforts.

Keywords

crowdfunding, Kickstarter, recommending systems, Twitter

Discipline

Artificial Intelligence and Robotics | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering; Intelligent Systems and Optimization

Publication

Proceedings of the 23rd international conference on World Wide Web

First Page

261

Last Page

270

ISBN

9781450327442

Identifier

10.1145/2566486.2568005

Publisher

Association for Computing Machinery

City or Country

Seoul, Korea

Download

Share

COinS