Scam warnings spread like vaccines to reduce scams in communities
Scam Town: Can Scam Education Spread Like a Vaccine?
Social and Information NetworksComputers and SocietyMultiagent Systems
Summary
Scam warnings often come from friends or family who have been targeted, but it was unclear if these warnings could spread widely enough to protect whole communities. The authors created a simulated town where each resident is a computer model that talks and warns others about scams. They found that while word of mouth helps, warnings don’t usually spread enough on their own to stop scams completely. Biggest improvements happened when official warnings reached most people and were then shared by residents, cutting scams roughly in half in simulations. These results suggest clear, easy-to-share scam messages reaching the right people can help protect communities.
What this means in practice
- •For public safety teams: Design scam prevention campaigns that combine official warnings with clear, shareable messages to maximize community-wide protection.
- •For customer service teams: Target scam alerts to older customers most likely to be contacted by scammers and encourage message sharing to reduce fraud losses.
Tested on simulated data.
Authors
Simiao Ren, Tommy Duong, Xingyu Shen, Jiaqi Gan, Tsang Ng, Ankit Raj, Kidus Zewde, Huaiyu Guo, Siyu Zhang
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.