A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction

We consider a tweet concatenation attack that 'retweet' semantically similar tweets to fool financial forecasting models. This repository is the official implementation of our paper.

Requirements

Run the following command to install requirements:

pip install -r requirements.txt

Dataset & Trained Victim Models

The preprocessed dataset, used resources and trained victim models used in the paper are publicly available at: dataset. resource and trained models.

Alternatively, run the following command to download and decompress the resources. It also creates the necessary folders used in the training and attacking.

bash downloader.sh

Attack & Evaluation

To run the attack and look into the results, run the following command with model arguements han, stocknet, tweetgru or tweetlstm:

bash attack.sh han

It conducts concatenation attack with perturbation of replacement for various budget via joint optimization. The results are saved in /log/attack. The attack uses our trained models. Change the arguments in the script to implement different attacks.

Training

To train the 4 victim models from the scratch, run this command with a model argument:

bash train.sh han

It trains the models with the same hyperparameters used in the paper. The training logs and checkpoints are save in /log/train and checkpoints respectively.

Highlighted Results

Effect of attack budget on Attack Success Rate (ASR)

Impact of the attack on portfolio PnL: trading simulation with initial value $10000 shows our attack causes additional loss of $3200 (32%) over two years.

Citation

@article{xie2022advtweet, 
  title={A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction},
  author={Xie, Yong and Wang, Dakuo and Chen, Pin-Yu and Jinjun, Xiong and Liu, Sijia and Koyejo, Oluwasanmi},
  journal={Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year={2022}
}

yonxie / AdvFinTweet