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 presents inSearch, 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.
翻译：Crowdfund为项目创始人提供了一个方便的接触在线投资者的途径。然而,对于创始人来说,找到最有潜力的投资者并成功地为其在众集供资平台上的项目筹集资金是困难的。一些基于机器的学习方法已经提出来建议投资者对特定众集供资项目的兴趣,但是他们没有为这些建议提供详细的解释,从而导致对预测投资者的信任减弱。为了帮助众集供资创始人找到真正感兴趣的投资者,我们与四名众集供资专家进行了半结构性的访谈,并在Search(视觉分析系统)上展示了一种视觉分析系统。在Search(Search)中,创始人得以在众集供资平台上以互动的方式寻找投资者。它支持通过利用图形神经网络来模拟投资者的偏好,对潜在投资者进行有效的概览。此外,它能够互动探索和比较不同投资者投资细节的时间演变。
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