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Journal of Social Computing

Keywords

crowdfunding, image-text fusion, GoFundMe

Abstract

Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign’s success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful.

Publisher

Tsinghua University Press

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