diff --git a/Twitter Sentiment Analysis/app.py b/Twitter Sentiment Analysis/app.py
new file mode 100644
index 0000000..d96b2c9
--- /dev/null
+++ b/Twitter Sentiment Analysis/app.py	
@@ -0,0 +1,87 @@
+import re 
+import tweepy 
+from tweepy import OAuthHandler 
+from textblob import TextBlob 
+  
+class TwitterClient(object): 
+    ''' 
+    Generic Twitter Class for sentiment analysis. 
+    '''
+    def __init__(self):
+        consumer_key = 'XXXXXXXXXXXXXXXXXXXXXXXX'
+        consumer_secret = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXX'
+        access_token = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXX'
+        access_token_secret = 'XXXXXXXXXXXXXXXXXXXXXXXXX'
+  
+        # attempt authentication 
+        try:
+            self.auth = OAuthHandler(consumer_key, consumer_secret)
+            self.auth.set_access_token(access_token, access_token_secret)
+            self.api = tweepy.API(self.auth) 
+        except: 
+            print("Error: Authentication Failed") 
+  
+    def clean_tweet(self, tweet):
+        '''
+        return ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)", " ", tweet).split()) 
+  
+    def get_tweet_sentiment(self, tweet): 
+        ''' 
+        Utility function to classify sentiment of passed tweet 
+        using textblob's sentiment method 
+        '''
+        # create TextBlob object of passed tweet text 
+        analysis = TextBlob(self.clean_tweet(tweet)) 
+        # set sentiment 
+        if analysis.sentiment.polarity > 0: 
+            return 'positive'
+        elif analysis.sentiment.polarity == 0: 
+            return 'neutral'
+        else: 
+            return 'negative'
+  
+    def get_tweets(self, query, count = 10):
+        tweets = [] 
+  
+        try: 
+            fetched_tweets = self.api.search(q = query, count = count)
+            for tweet in fetched_tweets:
+                parsed_tweet = {}
+                parsed_tweet['text'] = tweet.text 
+                parsed_tweet['sentiment'] = self.get_tweet_sentiment(tweet.text) 
+                if tweet.retweet_count > 0: 
+                    if parsed_tweet not in tweets: 
+                        tweets.append(parsed_tweet) 
+                else: 
+                    tweets.append(parsed_tweet) 
+            return tweets 
+  
+        except tweepy.TweepError as e: 
+            print("Error : " + str(e)) 
+  
+def main():
+    api = TwitterClient() 
+    tweets = api.get_tweets(query = 'Donald Trump', count = 200) 
+
+    ptweets = [tweet for tweet in tweets if tweet['sentiment'] == 'positive'] 
+
+    print("Positive tweets percentage: {} %".format(100*len(ptweets)/len(tweets))) 
+
+    ntweets = [tweet for tweet in tweets if tweet['sentiment'] == 'negative'] 
+
+    print("Negative tweets percentage: {} %".format(100*len(ntweets)/len(tweets))) 
+
+    print("Neutral tweets percentage: {} % \ 
+        ".format(100*(len(tweets) -(len( ntweets )+len( ptweets)))/len(tweets))) 
+  
+
+    print("\n\nPositive tweets:") 
+    for tweet in ptweets[:10]: 
+        print(tweet['text']) 
+
+    print("\n\nNegative tweets:") 
+    for tweet in ntweets[:10]: 
+        print(tweet['text']) 
+  
+if __name__ == "__main__": 
+    main() 
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