Identifying and Analyzing Cryptocurrency Manipulations in Social Media
This addresses fraud detection for cryptocurrency investors, though it is incremental as it builds on existing methods for social media analysis.
The paper tackles the problem of identifying cryptocurrency 'pump and dump' scams on social media by proposing a computational approach that detects these scams in real-time and predicts their success, while also analyzing bot activity, noting a significant increase during pump attempts.
Interest surrounding cryptocurrencies, digital or virtual currencies that are used as a medium for financial transactions, has grown tremendously in recent years. The anonymity surrounding these currencies makes investors particularly susceptible to fraud---such as "pump and dump" scams---where the goal is to artificially inflate the perceived worth of a currency, luring victims into investing before the fraudsters can sell their holdings. Because of the speed and relative anonymity offered by social platforms such as Twitter and Telegram, social media has become a preferred platform for scammers who wish to spread false hype about the cryptocurrency they are trying to pump. In this work we propose and evaluate a computational approach that can automatically identify pump and dump scams as they unfold by combining information across social media platforms. We also develop a multi-modal approach for predicting whether a particular pump attempt will succeed or not. Finally, we analyze the prevalence of bots in cryptocurrency related tweets, and observe a significant increase in bot activity during the pump attempts.