SANDS
This is an annonymous repository containing code and data necessary to reproduce the results published in "Semi-supervised Stance Detection of Tweets Via Distant Network Supervision" for the proposed method SANDS and compared baselines.
Steps to run SANDS
- Install the required packages mentioned here.
- Download and extract the data and place under the working directory
- Change directory to SANDS/SANDS/codes and run 'python3 run_model.py $dataname $splitsize $numclasses' where $dataname can be either INDIA or USA, $splitsize among 500, 1000, and, 1500. $numclasses currently support 5 and 7 for USA and INDIA arguments, respectively.