TY - GEN
T1 - Can title images predict the emotions and the performance of crowdfunding projects?
AU - Hou, Jian Ren
AU - Zhang, Jie Jennifer
AU - Zhang, Kunpeng
N1 - Funding Information:
Number of Backers: Backer is who contributes financial support to crowdfunding project. The unit is person for each finished crowdfunding project.
Publisher Copyright:
© 2019 IEEE Computer Society. All rights reserved.
PY - 2019
Y1 - 2019
N2 - Crowdfunding is a novel way to raise funds from individuals. However, taking Kickstarter for example, more than 60% of projects failed to reach the funding targets. Hence it is imperative to study how to improve the successfulness of the projects. From a design perspective, we intend to investigate that can the characteristics of title images of the projects on the search page of the crowdfunding website predict the performance of crowdfunding projects. We use objective standards to measure the aesthetic features of the title images. And we introduce emotions as important antecedents for the performance of a project. We used deep learning to extract the emotion metrics from the title images. Analysis results provide significant evidence that aesthetic attributes of images can predict emotion in images, and emotions, such as sadness and contentment, can predict the performance of crowdfunding projects. Our results provide both theoretical and practical values.
AB - Crowdfunding is a novel way to raise funds from individuals. However, taking Kickstarter for example, more than 60% of projects failed to reach the funding targets. Hence it is imperative to study how to improve the successfulness of the projects. From a design perspective, we intend to investigate that can the characteristics of title images of the projects on the search page of the crowdfunding website predict the performance of crowdfunding projects. We use objective standards to measure the aesthetic features of the title images. And we introduce emotions as important antecedents for the performance of a project. We used deep learning to extract the emotion metrics from the title images. Analysis results provide significant evidence that aesthetic attributes of images can predict emotion in images, and emotions, such as sadness and contentment, can predict the performance of crowdfunding projects. Our results provide both theoretical and practical values.
UR - http://www.scopus.com/inward/record.url?scp=85082294820&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082294820&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85082294820
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 4439
EP - 4448
BT - Proceedings of the 52nd Annual Hawaii International Conference on System Sciences, HICSS 2019
A2 - Bui, Tung X.
PB - IEEE Computer Society
T2 - 52nd Annual Hawaii International Conference on System Sciences, HICSS 2019
Y2 - 8 January 2019 through 11 January 2019
ER -