Memecoin fraud via telegram: a criminological big data approach

• In Event: Crypto & Darknet

Abstract

This study examines the intersection of cryptocurrency memecoin fraud, social media activity on Telegram, and price fluctuations, while also presenting a novel tool for systematically collecting and archiving data from Telegram channels. Fraud, particularly within the rapidly evolving cryptocurrency market, remains an understudied area within criminology, despite its growing societal and economic impact. Memecoins, often driven by speculative trading and community hype, have become a fertile ground for fraudulent activities, with Telegram emerging as a central platform for their promotion and coordination. By analysing the frequency and timing of coin mentions across Telegram channels, this research identifies patterns that correlate with abrupt price movements, which may indicate market manipulation or orchestrated pump-and-dump schemes. Preliminary findings reveal a significant relationship between social media activity and subsequent price volatility, underscoring the potential for such data to serve as an early warning system for fraudulent behaviour. This work not only advances understanding of fraud within the cryptocurrency space but also highlights the broader implications for criminological research, particularly in the digital age where social media platforms play a pivotal role in facilitating financial crime.

Central to this research is the development of a bespoke tool designed to automate the collection of Telegram data. Beginning with a small number of seed channels, the tool iteratively identifies and archives related channels, enabling users to construct a tailored dataset from minimal starting points. It efficiently captures all media shared within these channels, offering a comprehensive resource for analysis. The tool’s design prioritises flexibility and efficiency, minimising storage requirements while remaining adaptable to diverse research contexts where Telegram is a significant communication platform. This innovation not only supports the study of cryptocurrency fraud but also holds promise for broader criminological applications, such as investigating organised crime, illicit drugs, and other illicit activities facilitated through digital channels.

Authors

• Jack Cunliffe, University of Kent

• David Décary-Hétu, Université de Montréal

• Haiyue Yuan, School of Computing, University of Kent