# Identifying and Analyzing Cryptocurrency Manipulations in Social Media

arXiv: https://arxiv.org/abs/1902.03110 · HTML: https://mlsanity.com/paper/1902.03110/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2019.

## Built on by (most cited first, 8 of 8)

- [Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump](https://mlsanity.com/paper/2204.12929/) (2022)
- [Detecting Pump&Dump Stock Market Manipulation from Online Forums](https://mlsanity.com/paper/2301.11403/) (2023)
- [Machine Learning for Blockchain Data Analysis: Progress and Opportunities](https://mlsanity.com/paper/2404.18251/) (2024)
- [textscPerseus: Tracing the Masterminds Behind Cryptocurrency Pump-and-Dump Schemes](https://mlsanity.com/paper/2503.01686/) (2025)
- [Linear Laws of Markov Chains with an Application for Anomaly Detection in Bitcoin Prices](https://mlsanity.com/paper/2201.09790/) (2022)
- [Application of AI-based Models for Online Fraud Detection and Analysis](https://mlsanity.com/paper/2409.19022/) (2024)
- [Information Cascade Prediction under Public Emergencies: A Survey](https://mlsanity.com/paper/2404.01319/) (2024)
- [PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram](https://mlsanity.com/paper/2605.09431/) (2026)

## Abstract (arXiv)

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.