Including codes and data for the Summer 2020 Python Project.

The name of Project is Wag the Dog’ Media: Does the President Distract the Public When Issuing Executive Orders?"

Files Included:

• Scrapes all presidential orders from https://www.presidency.ucsb.edu by
  • its content,
  • issue no,
  • issue date, and
  • url since the presidentcy of Donald Trump.

• Created by \gencer_ExecutiveOrderScraping.py after scraping.

• Downloaded from http://www.trumptwitterarchive.com/
• Over 24 thousand Trump tweets, each tweet includes
  • content
  • number of likes
  • numbe of retweets

• Preprocesses executive orders.
• Creates the beginning and end dates of 1,3,5,7,11, and 15 days intervals around the executive orders
• Applies these intervals to \gencer_TrumpTweets.csv

• Processed version by \preprocessing_exeorder.py that includes
  • Intervals and Search Term results.

• Downloads nltk Twitter corpus data to train a logistic function for sentiment analysis (5000positive \ 5000negative)
• Trains a logistic regression based on the training data (the code from Coursera course: Natural Language Processing).
• Preprocesses each Trump tweet by
  • removing stop words,
  • removing punctuations,
  • stemming and tokenizing (the code from Coursera course: Natural Language Processing).
• Predicts the sentiment scores of each tweet

• Processed version by \sentiment_analysis_for_tweets.py that includes
  • Sentiment Score of each Tweet

• Runs the linear regressions
• Creates figures with estimates and confidence intervals

• Presentation of the Python project

• Includes all figures created by \dataanalysis_gencer.Rmd for the project.
• all in .jpg format.