Code for the paper "A Comparative Analysis of Stance Detection Approaches and Datasets"

This repository includes code for replicating six widely used baseline methods for target-specific stance detection.

Project Status - Active

Running instructions:

All the jupyter notebook are self-contained. To run, select the dataset you want to use in the first cell.

If using this code for your own research that you plan to publish, please cite the following article:

Parush Gera, Tempestt Neal. A Comparative Analysis of Stance Detection Approaches and Datasets. Proceedings of the EVAL4NLP workshop at Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP) 2022.

For more information, please e-mail Parush Gera at parush@usf.edu.