While human factors in fraud have been studied by the HCI and security communities, most research has been directed to understanding either the victims' perspectives or prevention strategies, and not on fraudsters, their motivations and operation techniques. Additionally, the focus has been on a narrow set of problems: phishing, spam and bullying. In this work, we seek to understand review fraud on e-commerce platforms through an HCI lens. Through surveys with real fraudsters (N=36 agents and N=38 reviewers), we uncover sophisticated recruitment, execution, and reporting mechanisms fraudsters use to scale their operation while resisting takedown attempts, including the use of AI tools like ChatGPT. We find that countermeasures that crack down on communication channels through which these services operate are effective in combating incentivized reviews. This research sheds light on the complex landscape of incentivized reviews, providing insights into the mechanics of underground services and their resilience to removal efforts.

翻译：尽管人机交互与安全社区已研究欺诈中的人为因素，但多数研究聚焦于理解受害者视角或防范策略，而非欺诈者自身、其动机及运作手法。此外，研究范围局限于少数问题领域：钓鱼欺诈、垃圾信息与网络霸凌。本研究试图通过人机交互视角理解电商平台评论欺诈行为。通过对真实欺诈者（36名中介与38名评论员）的问卷调查，我们揭示了欺诈者用于规模化运作并抵御封禁的复杂招募、执行与报告机制，包括使用ChatGPT等人工智能工具。研究发现，打击此类服务运营通信渠道的反制措施能有效抑制激励性评论。本研究揭示了激励评论的复杂图景，为理解地下服务的运作机制及其对抗移除行为的韧性提供了洞见。