framing-police-violence

Authors: Caleb Ziems, Diyi Yang

This repository contains data links and code for the paper:

Ziems, C. & Yang, D. (2021). To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violence In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP).

@inproceedings{ziems2021protect,
 author = {Ziems, Caleb and Yang, Diyi},
 booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
 title = {{To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violence}},
 year = {2021}
}

Prerequisites - Environment

• anaconda Create main project environment

conda create --name framing-pv python=3.7
conda activate dragnet
pip install -r requirements_dragnet.txt
conda deactivate

conda create --name coref python=3.7
conda activate coref
pip install -r requirements_coref.txt
conda deactivate

conda create --name framing-pv python=3.7
conda activate framing-pv
pip install -r requirements.txt
python -m spacy download en_core_web_sm

Project Pipeline

All data is contained in a zip file in the Drive directory

1. Download all data and setup repo by running bash populate_repo.sh

2. Run python 01_pull_shooting_articles.py to scrape news articles on police killings

3. Clean the retrieved articles by first switching to conda activate dragnet and running python 03_dragnet_clean.py --input_glob "data/raw/shootings-articles/*/*.html" --output "data/raw/shootings-txt"

4. Return to conda activate framing-pv and compile all scraped shooting articles with their political leanings by running python 04_build_shooting_df.py

5. Switch to conda activate coref and extract all frames by running python 05_framing_functions.py

6. Switch back to conda activate framing-pv and run python 06_clean_framing_file.py to generate the composite file for framing analysis

7. Run the analyses in paper-analysis.ipynb and protest-granger.ipynb