Participatory budgeting is a democratic innovation that empowers citizens to propose and vote on public investment projects. While researchers in computer science focused on improving the voting phase of this process, in this work we aim to support organizers of participatory budgeting campaigns to manage large volumes of project proposals at the submission stage. We propose a privacy-preserving approach to predict which proposals are likely to be funded, using only projects' textual descriptions and anonymous historical voting records, without relying on voter demographics or personally identifiable information.

翻译：参与式预算是一种民主创新机制，赋予公民提议并投票决定公共投资项目的能力。尽管计算机科学领域的研究者主要关注改进该流程中的投票阶段，但本研究旨在支持参与式预算活动的组织者在提案提交阶段管理海量项目提案。我们提出一种隐私保护方法，仅利用项目的文本描述和匿名历史投票记录（不依赖选民人口统计信息或个人可识别信息）来预测哪些提案可能获得资助。