Awesome

Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations

This codebase contains the python scripts for MAN-S, the model for the EMNLP 2020 paper link.

Environment & Installation Steps

Python 3.6, Pytorch, and networkx.

pip install -r requirements.txt

Dataset and Preprocessing

Download the dataset from here.

Follow link to generate tweet embeddings.

Generate graph

Follow link to generate the graph.

Run

Execute the following python command to train MAN-SF:

python train.py

Cite

Consider citing our work if you use our codebase

@inproceedings{sawhney-etal-2020-deep,
    title = "Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations",
    author = "Sawhney, Ramit  and
      Agarwal, Shivam  and
      Wadhwa, Arnav  and
      Shah, Rajiv Ratn",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.676",
    doi = "10.18653/v1/2020.emnlp-main.676",
    pages = "8415--8426"}