trump_sentiment.py

import tweepy
import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
import matplotlib.pyplot as plt

# Consumer keys and access tokens, used for OAuth
consumer_key = ''
consumer_secret = ''
access_token = ''
access_token_secret = ''

# OAuth process, using the keys and tokens
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)

user = "realDonaldTrump"

# Creation of the actual interface, using authentication
api = tweepy.API(auth)

sid = SentimentIntensityAnalyzer()
D = {'cnn':[],'nbc':[],'new york times':[],'washington post':[],'cbs':[],'abc':[],'time':[],'fox':[]}

for status in tweepy.Cursor(api.user_timeline, screen_name='@'+user).items():
    tweet = status.text#.encode('utf-8',errors='ignore')
    #print(tweet)
    ss = sid.polarity_scores(tweet)['compound']
    
    for outlet in D.keys():
        if outlet in tweet.lower():
            D[outlet] += [ss]
    
for outlet in D.keys():
    if len(D[outlet])>0:
        avg = sum(D[outlet])/len(D[outlet])
    else:
        avg = 0
    
    D[outlet] = avg

plt.bar(range(len(D)), D.values(), align='center')
plt.xticks(range(len(D)), list(D.keys()), rotation=17)

plt.xlabel("News Outlets")
plt.ylabel("Average Sentiment")
plt.ylim(-0.4,0.2)
plt.grid()

plt.show()