Crowdsourcing services, such as Waze and Google Maps, leverage a mass of mobile users to learn massive point-of-interest (PoI) information while traveling and share it as a public good. Given that crowdsourced users mind their travel costs and possess various preferences over the PoI information along different paths, we formulate the problem as a novel non-atomic multi-path routing game with positive network externalities among users in social information sharing, which distinguishes itself from the routing game literature. In the absence of any incentive design, our price of anarchy (PoA) analysis shows that users' selfish routing on the path with the lowest cost will limit information diversity and lead to an arbitrarily large efficiency loss from the social optimum. This motivates us to design effective incentive mechanisms to remedy while upholding desirable properties such as individual rationality, incentive compatibility, and budget balance for practical feasibility. Moreover, our mechanisms are designed with incomplete information, as they do not rely on individual user's path preferences, thereby ensuring user privacy. To start with, we present a non-monetary mechanism called Adaptive Information Restriction (AIR) that imposes fractions on users' access to the public good as an indirect penalty. By adapting penalty fractions to the actual user flows along different paths, our AIR achieves the first PoA of $\frac{1}{4}$ for the problem. Then, we delve into a monetary mechanism called Adaptive Side-Payment (ASP) that charges or rewards side payments over users choosing certain paths. With those side payments well-tailored, ASP significantly improves the PoA to $\frac{1}{2}$.

翻译：众包服务（如Waze和谷歌地图）借助大量移动用户在出行过程中学习海量兴趣点（PoI）信息，并将其作为公共物品共享。考虑到众包用户关注出行成本，并对不同路径上的PoI信息存在多样化偏好，我们将该问题建模为一种新型非原子多路径路由博弈，其中用户在社交信息共享中呈现正网络外部性，这使其区别于传统路由博弈文献。在无任何激励设计的情况下，我们的无政府价格（PoA）分析表明：用户自私地选择最低成本路径将限制信息多样性，并导致与最优社会效率间的任意大损失。这促使我们设计有效的激励补救机制，同时保持实际可行性所需的个体理性、激励相容性和预算平衡等理想特性。此外，我们的机制基于不完全信息设计，不依赖单个用户的路径偏好，从而保障用户隐私。首先，我们提出一种非货币机制——自适应信息限制（AIR），通过限制用户对公共物品的访问比例作为间接惩罚。通过根据各路径实际用户流量动态调整惩罚比例，AIR实现了该问题的首个PoA值为$\frac{1}{4}$。随后，我们深入探讨货币机制——自适应侧支付（ASP），对选择特定路径的用户收取或奖励侧支付。通过精心设计这些侧支付，ASP将PoA显著提升至$\frac{1}{2}$。