
Discover how cryptocurrency giveaway scams operate, convert victims, and generate millions. Learn the latest insights from social media and blockchain analysis.
Cryptocurrency has exploded in popularity, driven by promises of decentralized finance and quick fortunes. Unfortunately, this has also drawn the attention of scammers. In the paper “Give and Take: An End-To-End Investigation of Giveaway Scam Conversion Rates” (2024), authored by Enze Liu, George Kappos, and others, the research investigates the mechanisms behind cryptocurrency giveaway scams and quantifies their financial impact. This study leverages data from Twitter, YouTube, and blockchain records to assess how these scams are structured and how successful they are at converting viewers into victims. The findings are both alarming and insightful, shedding light on an insidious form of fraud in the digital age.
The primary research question explored in this paper is how cryptocurrency giveaway scams convert unsuspecting users into victims. The methodology includes gathering data from social media platforms, such as Twitter and YouTube, where these scams are frequently promoted. The researchers gathered tweets and livestreams associated with scam sites and extracted the relevant cryptocurrency addresses from the scam promotions. They then tracked payments to these addresses using blockchain data, focusing primarily on Bitcoin (BTC), Ethereum (ETH), and Ripple (XRP).
Their data collection covered over 457,000 tweets and 2,069 YouTube livestreams. Through their analysis, the researchers found that 1 in 1000 scam tweets resulted in a victim, while approximately 4 in 100,000 YouTube livestream views led to a payment to scammers. Over the study period, these scammers raked in $4.62 million across various platforms, with Twitter yielding $2.7 million and YouTube contributing $1.9 million. Notably, the conversion rates varied significantly between platforms, reflecting differences in user interaction dynamics.
The study also delved into the behavior of both victims and scammers. For instance, they found that most victims used centralized exchanges to transfer funds, while scammers were adept at cycling through multiple cryptocurrency addresses to avoid detection. Additionally, the paper highlights how a small number of high-value transactions accounted for the bulk of scam revenue, a pattern similar to that found in other types of digital fraud.

The strengths of this study lie in its comprehensive approach and multi-platform data collection. By combining data from social media with blockchain analysis, the authors provide a full-spectrum view of how cryptocurrency scams unfold from start to finish. This end-to-end approach, coupled with the large dataset, offers robust insights into the scale and mechanics of these scams.

However, there are limitations that temper the findings. First, the researchers acknowledged gaps in the completeness of the Twitter dataset, which might have caused them to underestimate scam volumes. Likewise, the YouTube and Twitter datasets were collected during different time periods, which may have led to inconsistencies in assessing scammer behavior and profitability across platforms. Additionally, the conversion rates are only approximations since factors like tweet visibility and YouTube viewer engagement are difficult to quantify with precision.
In terms of originality, this study stands out by providing the first rigorous estimate of scam conversion rates in the cryptocurrency space. Previous studies had been largely anecdotal or limited to specific platforms. This paper not only improves our understanding of the profitability of these scams but also opens avenues for future research and intervention strategies.
Perhaps the most surprising aspect of the research is the sheer profitability of these scams, particularly given the low conversion rates. A conversion rate of 0.12% per tweet and 0.0039% per YouTube viewer seems negligible, but the vast reach of these platforms means that even such small percentages translate into significant sums of money. In particular, the fact that just a handful of large payments contributed to the majority of the revenue highlights the “whale” effect common in digital fraud. This revelation raises the chilling possibility that scammers may only need a few gullible victims with deep pockets to make their schemes worthwhile.

The implications of this research are far-reaching. By revealing how these scams operate and identifying bottlenecks in the scam lifecycle, the study paves the way for more effective interventions. One of the most promising points of intervention, as noted by the authors, is the centralized exchanges through which many victims transfer funds. If exchanges can implement stricter security protocols or warnings when users attempt to send large amounts to suspect addresses, this could help curb the impact of these scams.
Furthermore, the research raises important questions about the role of social media platforms. Twitter and YouTube are integral to the spread of these scams, and better detection systems are needed to flag fraudulent content before it reaches wide audiences. This is especially urgent given that scammers are continuously evolving their tactics. The findings also suggest future research could focus on more advanced blockchain analysis to uncover scam networks and link seemingly disparate scams.
The “Give and Take” study shines a critical light on the dark side of the cryptocurrency boom. The researchers have meticulously documented how giveaway scams unfold across social media platforms, revealing their surprisingly lucrative nature despite relatively low conversion rates. This research is invaluable for policymakers, cybersecurity experts, and the general public as it emphasizes the need for a multi-faceted approach to combat these scams. From improved detection on social media to better consumer protections at cryptocurrency exchanges, there is much that can be done to stem the tide of fraud. Overall, this paper is a must-read for anyone interested in the intersection of cryptocurrency, cybersecurity, and online fraud.
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Ervin Zubic
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