Charting the Landscape of Online Cryptocurrency Manipulation

Abstract

Cryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we chart the online cryptocurrency landscape across multiple platforms. To reach our goal, we collected a large dataset, composed of more than 50M messages published by almost 7M users on Twitter, Telegram and Discord, over three months. We performed bot detection on Twitter accounts sharing invite links to Telegram and Discord channels, and we discovered that more than 56% of them were bots or suspended accounts. Then, we applied topic modeling techniques to Telegram and Discord messages, unveiling two different deception schemes -"pump-and-dump" and "Ponzi" -and identifying the channels involved in these frauds. Whereas on Discord we found a negligible level of deception, on Telegram we retrieved 296 channels involved in pump-and-dump and 432 involved in Ponzi schemes, accounting for a striking 20% of the total. Moreover, we observed that 93% of the invite links shared by Twitter bots point to Telegram pump-and-dump channels, shedding light on a little-known social bot activity. Charting the landscape of online cryptocurrency manipulation can inform actionable policies to fight such abuse.

Tracing Cryptocurrency Scams: Clustering Replicated Advance-Fee and Phishing Websites

“…Those orchestrating such schemes announce the certain cryptocurrency and participants buy with the hope that they can sell at a higher price [10]. Participants are usually made aware of such schemes through invite links, distributed on mass by automated social media accounts [11].…”

Down the bot hole: actionable insights from a 1-year analysis of bots activity on Twitter

“…False narratives, fake accounts, low-credibility news sources, state-sponsored operators, and so on and so forth: The online ecosystem landscape appears loaded with threats and malicious entities disposed to undermine the integrity of social media discussions. Among those, bots (i.e., automated and softwarecontrolled accounts) [23,12] and trolls (i.e., human operators often statesponsored) [61,35,3] have been recognized as the main responsible actors of manipulation and misinformation operations in diverse contexts [18], ranging from finance [38,14,51] to public health [21,58], in which the rise of infodemics (i.e., the widespread diffusion of unverified information and conspiracy theories) during the Covid-19 outbreak represents the latest milestone of the misinformation age [63]. Moreover, the abusive behavior of these malicious actors received enormous resonance in the political domain [33,5,37,29,2,4,25,62,34], where the abuse of social platforms has put under threat the effective fulfillment of the democratic process, other than creating worldwide concerns for the integrity of voting events [47,7,49,3,40,19,28,46,54,48,6,27,43,41].…”

“…Nevertheless, in the last few years, researchers offered several approaches to identify bots [52,59,15,36,42,13,9,50,11], while solutions for unveiling the activity of trolls have been recently proposed [35,1]. Other studies focused on the detection of collective and inauthentic behaviors of malicious accounts to uncover coordinated campaigns [45,38,39] and suspicious content diffusion [31,26,60]. However, social media abuse persists and the online ecosystem still presents a mix of organic and malicious users [34,32], where the former class still demonstrates a moderate capability to identify the latter [56].…”