Understanding Scam Trends and Rail Paths from Reddit Self-Disclosure Narratives
2026-06-15 • Computation and Language
Computation and LanguageComputational Engineering, Finance, and ScienceComputers and Society
AI summaryⓘ
The authors studied online scams as stories with multiple steps rather than one-time events. They created a dataset from Reddit posts between 2023 and 2025 that discuss scams, labeling parts of scam processes like identity and payment using a mix of automated and human methods. Their analysis showed that scams usually involve several different steps and that the types of scams and how people discuss them change over time. They also found that Reddit communities are giving more detailed support to scam victims as time goes on. This research helps with creating fake scam data for training AI and understanding scam risks, but its findings might not apply to other websites.
online scamsmulti-stage processRedditself-disclosure narrativesdataset annotationscam railslarge language modelstopic modelingcommunity supportscam risk assessment
Authors
Yangjun Zhang, Mirko Bottarelli, Mark Hooper, Carsten Maple
Abstract
Online scam behavior is inherently multi-stage, and the lifecycle includes temporally ordered rails and events rather than isolated signals. Existing works analyze characteristics of scam types and rails, but they do not track scam trends across years. Moreover, the work on the relations between rails is hampered due to the lack of open-source datasets with annotations and coverage of different scam types. To address these gaps, we build a dataset to analyze the yearly trend of scam characteristics and rail paths using Reddit self-disclosure narratives from 2023 to 2025. We collect 21,304 posts from scam-related subreddits with at least one rail among identity, communication, platform, and payment for trend analysis by heuristic annotation. Then, we label 1,800 posts containing explicit or recoverable scam chains by an LLM-assisted method for scam path analysis. The method is evaluated with human annotation. Lastly, we run a topic model on the comments of the posts to analyze the community support behavior. The results reveal that scam processes are predominantly multi-rail. Across years, different scam types and rail components dominate. Different scam types vary systematically in path complexity. Reddit support behaviors have become more detailed over time. This work supports synthetic scam chain data simulation and AI-related scam risk assessment, though findings may not generalise to other platforms.