This repository contains the replication files of the following publication:
Why Justifications of Claims Matter for Understanding Party Positions. In: Proceedings of the 2nd Workshop on Computational Linguistics for Political Text Analysis. 2022. Nico Blokker, Tanise Ceron, André Blessing, Erenay Dayanik, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa and Sebastian Padó.
In detail it contains the main data set (MaCov21.csv), the script used
for analysis (Analysis.R), as well as the calculations for cosine
similarities based on SBERT (see below).
To interact and visualize the data visit: https://mardy.shinyapps.io/MaCov21_dashboard/
In order to run the cosine similarity among frames grouped by claim
categories in WoM21 (WoM_avg_justifications_v2.csv), run:
python3 cosine_sim_sbert_wom.py
If you want to run the cosine similarity among claims grouped by claims
in MaCov (MaCov_avg_claims_v2.csv), run:
python3 cosine_sim_sbert_maco.py --column claim_quote --group_by claim
To run cosine similarity among frames grouped by claims in MaCov
(MaCov_avg_frames_grouped_by_claims.csv):
python3 cosine_sim_sbert_maco.py --column frame_quote --group_by claim
Lastly, for running cosine similarity among frames grouped by frames
(MaCov_avg_frames_grouped_by_frames.csv), execute:
python3 cosine_sim_sbert_maco.py --column frame_quote --group_by frame