mlsanityData to 14 Oct 2026

Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses

arXiv 2407.09480 ↗First posted 24 Apr 2024econ.GN cs.AI cs.CLcited by 1

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Abstract (arXiv)

While small businesses are increasingly turning to online crowdfunding platforms for essential funding, over 40% of these campaigns may fail to raise any money, especially those from low socio-economic areas. We utilize the latest advancements in AI technology to identify crucial factors that influence the success of crowdfunding campaigns and to improve their fundraising outcomes by strategically optimizing these factors. Our best-performing machine learning model accurately predicts the fundraising outcomes of 81.0% of campaigns, primarily based on their textual descriptions. Interpreting the machine learning model allows us to provide actionable suggestions on improving the textual description before launching a campaign. We demonstrate that by augmenting just three aspects of the narrative using a large language model, a campaign becomes more preferable to 83% human evaluators, and its likelihood of securing financial support increases by 11.9%. Our research uncovers the effective strategies for crafting descriptions for small business fundraising campaigns and opens up a new realm in integrating large language models into crowdfunding methodologies.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 62 references that are in the map. First posted on arXiv 24 Apr 2024.

Builds on

8 of 62 references.

References · 8

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
  3. 2013Crowdsourcing a Word-Emotion Association Lexiconcited by 196
  4. 2016Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussionscited by 110
  5. 2020What Contributes to a Crowdfunding Campaign's Success? Evidence and Analyses from GoFundMe Datacited by 4
  6. 2020Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economycited by 2
  7. 2015Making the Most of Tweet-Inherent Features for Social Spam Detection on Twittercited by 1
  8. 2019A cross-sectional study of social inequities in medical crowdfunding campaigns in the United Statescited by 1

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