# Detecting Pump&Dump Stock Market Manipulation from Online Forums

arXiv: https://arxiv.org/abs/2301.11403 · HTML: https://mlsanity.com/paper/2301.11403/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 39 references that are in the map.
- First posted on arXiv 26 Jan 2023.

## Builds on (most cited first, 5 of 5)

- [A Unified Approach to Interpreting Model Predictions](https://mlsanity.com/paper/1705.07874/) (2017)
- [XGBoost: A Scalable Tree Boosting System](https://mlsanity.com/paper/1603.02754/) (2016)
- [Empath: Understanding Topic Signals in Large-Scale Text](https://mlsanity.com/paper/1602.06979/) (2016)
- [Identifying and Analyzing Cryptocurrency Manipulations in Social Media](https://mlsanity.com/paper/1902.03110/) (2019)
- [Identifying Users with Opposing Opinions in Twitter Debates](https://mlsanity.com/paper/1402.7143/) (2014)

## Built on by (most cited first, 3 of 3)

- [PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram](https://mlsanity.com/paper/2605.09431/) (2026)
- [ReguSim: Evaluating LLM Agent Rule Grounding in Financial Compliance](https://mlsanity.com/paper/2608.19974/) (2026)
- [Contagion on the Trading Floor: How Adversarial Signals Spread in Multi-Agent Trading Systems](https://mlsanity.com/paper/2609.19789/) (2026)

## Abstract (arXiv)

The intersection of social media, low-cost trading platforms, and naive investors has created an ideal situation for information-based market manipulations, especially pump&dumps. Manipulators accumulate small-cap stocks, disseminate false information on social media to inflate their price, and sell at the peak. We collect a dataset of stocks whose price and volume profiles have the characteristic shape of a pump&dump, and social media posts for those same stocks that match the timing of the initial price rises. From these we build predictive models for pump&dump events based on the language used in the social media posts. There are multiple difficulties: not every post will cause the intended market reaction, some pump&dump events may be triggered by posts in other forums, and there may be accidental confluences of post timing and market movements. Nevertheless, our best model achieves a prediction accuracy of 85% and an F1-score of 62%. Such a tool can provide early warning to investors and regulators that a pump&dump may be underway.