arXiv cs.CY· Simiao Ren, Tommy Duong, Xingyu Shen, Jiaqi Gan, Tsang Ng, Ankit Raj, Kidus Zewde, Huaiyu Guo, Siyu Zhang·· 12 小时前AI 评分36
Scam Town：诈骗教育能否像疫苗一样在社区传播？
Scam Town: Can Scam Education Spread Like a Vaccine?
AI 导读
研究者构建了由大语言模型扮演居民的模拟社区 Scam Town，让诈骗中心致电居民、居民之间互相提醒。在 80 个模拟城镇中，日常口耳相传使被骗人数减少约五分之一，但每条警告平均带出的新警告不足一条，无法自行“病毒式”扩散。当银行、老年中心或机构的官方警告覆盖多数居民并引发讨论时，模拟中诈骗减少约一半；作者强调居民是语言模型替身，结论应视为待真人验证的预测。
正文
Abstract:Most older adults who hear a warning about scams hear it from someone they know: a relative, a neighbour, or a friend who was targeted. Yet research on scam prevention almost always studies one person at a time. We ask whether scam awareness can spread through a community and protect it the way a vaccine does, since a warning protects whoever hears it and can be passed on. To find out, we built Scam Town, a simulated community in which a large language model plays each resident. Scam centres phone the residents, and after a call a resident can warn the people they know. Word of mouth helped, but it did not take off on its own: each warning led to fewer than one more, so a community cannot count on warnings "going viral". Across 80 simulated towns, everyday talk cut the number of people scammed by roughly a fifth. The largest gains came when an official warning, from a bank, a senior centre, or an agency, reached most of a town and residents then talked about it: in simulation (a combination we did not test live) the two together cut scams by about half. Protection was greatest when warnings reached the people scammers actually call, who here were older residents. Because our residents are language-model stand-ins rather than real people, we treat these findings as predictions to test with people, not as proof. They point to a simple recipe for scam education: give people a clear story they can retell, design campaigns to be passed along, and reach first those most likely to be called.
| Comments: | 28 pages, 12 figures, 11 tables |
| Subjects: | Social and Information Networks (cs.SI); Computers and Society (cs.CY); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2610.25040 [cs.SI] |
| (or arXiv:2610.25040v2 [cs.SI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.25040 arXiv-issued DOI via DataCite |
Submission history
From: Simiao Ren [view email]
[v1]
Sun, 18 Oct 2026 06:00:19 UTC (3,909 KB)
[v2]
Sat, 24 Oct 2026 20:59:53 UTC (3,909 KB)
来源：arXiv cs.CY · arxiv.org