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README.md
README.md
 
 
all_floyd_cleaned_final.xlsx
all_floyd_cleaned_final.xlsx
 
 
floyd_tweets_by_congressional_districts.png
floyd_tweets_by_congressional_districts.png
 
 
floyd_tweets_by_date.png
floyd_tweets_by_date.png
 
 
merge_tweet_cd.R
merge_tweet_cd.R
 
 
negbin_coef_plot.png
negbin_coef_plot.png
 
 
negbin_pred_party.png
negbin_pred_party.png
 
 
piechart_total_tweets.png
piechart_total_tweets.png
 
 
regression.R
regression.R
 
 
scatterplot.png
scatterplot.png
 
 
stm_model.R
stm_model.R
 
 
topic_frequency.png
topic_frequency.png
 
 
topic_frequency_by_party.png
topic_frequency_by_party.png
 
 
topic_model.ipynb
topic_model.ipynb
 
 
topic_words.png
topic_words.png
 
 
tweet_map_cd.R
tweet_map_cd.R
 
 
twitter_scrape_and_count.py
twitter_scrape_and_count.py
 
 

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This document the empirical analysis of my published paper "Party Polarization in Digital Fingerprints: Tracing Politicians' Social Media Posts on the George Floyd Protests" on Party Politics.

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Twitter API; Natural Language Processing

journals.sagepub.com/doi/full/10.1177/13540688241287901

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apinatural-language-processingtopic-modeling

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