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Predicting crowdfunding project success based on backers' language preferences

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  • Qianzhou Du
  • Jing Li
  • Yanqing Du
  • G. Alan Wang
  • Weiguo Fan

Abstract

Project success is critical in the crowdfunding domain. Rather than the existing project‐centric prediction methods, we propose a novel backer‐centric prediction method. We identify each backer's preferences based on their pledge history and calculate the cosine similarity between backer's preferences and the project as each backer's persuasibility. Finally, we aggregate all the backers' persuasibility to predict project success. To validate our method, we crawled data on 183,886 projects launched during or before December 2014 on Kickstarter, a crowdfunding website. We selected 4,922 backers with a total of 442,793 pledges to identify backers' preferences. The results show that a backer is more likely to be persuaded by a project that is more similar to the backer's preferences. Our findings not only demonstrate the efficacy of backers' pledge history for predicting crowdfunding project success but also verify that a backer‐centric method can supplement the existing project‐centric approaches. Our model and findings enable crowdfunding platform agencies, fund‐seeking entrepreneurs, and investors to predict the success of a crowdfunding project.

Suggested Citation

  • Qianzhou Du & Jing Li & Yanqing Du & G. Alan Wang & Weiguo Fan, 2021. "Predicting crowdfunding project success based on backers' language preferences," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(12), pages 1558-1574, December.
    • Handle: RePEc:bla:jinfst:v:72:y:2021:i:12:p:1558-1574
    DOI: 10.1002/asi.24530
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    References listed on IDEAS

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    1. Teng Ye & Jingnan Zheng & Junhui Jin & Jingyi Qiu & Wei Ai & Qiaozhu Mei, 2024. "Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses," Papers 2407.09480, arXiv.org.

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