Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2022

Abstract

Crowdfunding provides project founders with a convenient way to reach online investors. However, it is challenging for founders to find the most potential investors and successfully raise money for their projects on crowdfunding platforms. A few machine learning based methods have been proposed to recommend investors’ interest in a specific crowdfunding project, but they fail to provide project founders with explanations in detail for these recommendations, thereby leading to an erosion of trust in predicted investors. To help crowdfunding founders find truly interested investors, we conducted semi-structured interviews with four crowdfunding experts and presentsinSearch, a visual analytic system. inSearch allows founders to search for investors interactively on crowdfunding platforms. It supports an effective overview of potential investors by leveraging a Graph Neural Network to model investor preferences. Besides, it enables interactive exploration and comparison of the temporal evolution of different investors’ investment details.

Keywords

Visual Analytics, Crowdfunding, Comparative Analysis

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceeding of the Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, New Orleans, LA USA, April 29 - May 5

First Page

1

Last Page

6

Identifier

10.1145/3491101.3519725

Publisher

Association for Computing Machinery

City or Country

New York

Additional URL

https://doi.org/10.1145/3491101.3519725

Download

Share

COinS