利用人工智能解锁小企业的众筹成功路径
Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses
AI总结：
针对小企业众筹项目超40%失败的问题，研究利用AI识别众筹成功关键因素，构建的机器学习模型预测准确率达81.0%，并通过大语言模型优化三方面文本描述，使项目获资可能性提升11.9%，为众筹文案提供有效策略。
摘要：
尽管小企业越来越多地转向在线众筹平台获取关键资金，但超过40%的此类众筹项目可能筹不到任何资金，尤其是来自低社会经济地区的项目。我们利用AI技术的最新进展，识别影响众筹项目成功的关键因素，并通过战略性优化这些因素来提升其筹资成果。我们表现最佳的机器学习模型主要基于项目的文本描述，可准确预测81.0%的众筹项目的筹资结果。通过对该机器学习模型进行解读，我们能够在项目启动前提供改进文本描述的可操作建议。我们证明，仅使用大语言模型增强叙事的三个方面，众筹项目就会更受83%的人类评估者青睐，其获得资金支持的可能性提升11.9%。我们的研究揭示了小企业筹资项目撰写描述的有效策略，也开辟了将大语言模型融入众筹方法学的新领域。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
