报告题目：Dynamic Persuasion Strategies for Mitigating the Spread of Fake Content

报 告 人：李文娟

报告时间：2026年10月12日（星期一）10:00-11:30

报告地点：明哲楼517

主办单位：东北财经大学现代供应链管理研究院

【报告人简介】

李文娟现为香港科技大学商学院运营管理博士后，在香港博士研究生奖学金计划（HKPFS）资助下完成香港科技大学运营管理博士阶段学习，师从 Dongwook Shin 教授。此前获约翰斯·霍普金斯大学金融学硕士学位和中国科学技术大学管理学学士学位。研究方向包括数字平台与内容市场、信息设计、社会学习及生成式人工智能，主要运用博弈论、动态规划和贝叶斯说服等方法开展研究。以第一作者身份撰写的论文已获 Manufacturing & Service Operations Management 接收，并获2025年POMS香港分会最佳学生论文竞赛荣誉奖（Honorable Mention）。

【摘要】

How can digital content platforms design information disclosure policies to shape consumers’ engagement with potentially fake content? We develop a dynamic information design model in which the platform and consumers initially face uncertainty about content veracity. The platform can conduct random inspections and strategically signal the results to maximize revenue. We characterize the optimal public and private disclosure policies and show that both strategically delay disclosure, increasing platform revenue but also consumers’ exposure to fake content. Unlike public disclosure, the optimal private policy selectively reveals inspection results to a subset of consumers. It therefore generates higher revenue but significantly undermines consumer welfare. We then examine strategies for mitigating fake content while maintaining profitability. Optimizing the platform’s inspection capability raises profits but fails to curb the spread of fake content. By contrast, subscriptions and government penalties can reduce the spread of fake content while enhancing platform revenue. These findings reveal the tension between platform profitability and misinformation mitigation and offer implications for the design of disclosure mechanisms and regulatory policies.