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.

翻译：社交媒体、低交易成本平台与缺乏经验的投资者相结合，为基于信息的市场操纵（尤其是拉高出货）创造了理想条件。操纵者首先吸纳小盘股，然后在社交媒体上散布虚假信息以推高其价格，并在股价达到峰值时抛售。我们收集了一组价格与成交量形态具有拉高出货特征样的股票数据集，以及与该类股票初始价格上涨时间同步的社交媒体帖子数据。基于这些数据，我们构建了根据社交媒体帖子语言内容预测拉高出货事件的模型。这面临多重困难：并非每篇帖子都能引发预期的市场反应，部分拉高出货事件可能由其他论坛的帖子触发，帖子发布时间与市场波动之间也可能存在偶然巧合。尽管如此，我们最优模型的预测准确率达到85%，F1分数为62%。此类工具可为投资者和监管机构提供早期预警，提示可能正在发生的拉高出货行为。