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This repository was archived by the owner on Dec 22, 2023. It is now read-only.

Commit 5e66e80

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Twitter Sentiment Analysis based on hashtag
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## Twitter Sentiment Analyis
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### This script fetches 500 most recent tweets based on a single hashtag input, classifies the tweets based on sentiment polarity of either 'Positive', 'Negative' or 'Neutral' and writes the output to a .xls script.
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### Pre-requisites
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This script uses the twitter API called tweepy. For this you will require a set of access token and consumer keys. Following steps show you how to obtain these credentials:
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– Login to twitter developer section
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– Go to "Create an App"
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– Fill the details of the application.
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– Click on Create your Twitter Application
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– Details of your new app will be shown along with consumer key and consumer secret.
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– Click on "Create my access token" to obtain access token.
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### How to use this script?
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1. Make sure all the requirements for the script are present in your system by running:
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pip install -r requirements.txt
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2. Enter the following values in 'credentials.yaml' based on access/consumer tokens obtained above:
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- consumer_key
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- consumer_secret
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- access_token
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- access_token_secret
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3. Run the following command (replace #hashtag with # of your choice):
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python twitter_sentiment_analysis.py #hashtag
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3. Open Sentiment_Analysis.xls to see analysed and categorised tweets
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### Author
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[Schezeen Fazulbhoy](https://github.com/schezfaz)
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consumer_key: ''
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consumer_secret: ''
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access_token: ''
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access_token_secret: ''
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atomicwrites==1.4.0
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attrs==19.3.0
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autogui==0.1.8
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certifi==2020年6月20日
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chardet==3.0.4
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click==7.1.2
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colorama==0.4.3
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comtypes==1.1.7
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idna==2.10
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joblib==0.16.0
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more-itertools==8.4.0
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MouseInfo==0.1.3
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nltk==3.5
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oauthlib==3.1.0
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packaging==20.4
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Pillow==7.2.0
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pluggy==0.13.1
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py==1.9.0
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PyAutoGUI==0.9.50
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pycparser==2.20
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PyGetWindow==0.0.8
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PyMsgBox==1.0.8
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pyparsing==2.4.7
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pyperclip==1.8.0
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PyRect==0.1.4
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PyScreeze==0.1.26
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PySocks==1.7.1
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pytest==5.4.3
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pythonnet==2.5.1
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PyTweening==1.0.3
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pywin32==228
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pywinauto==0.6.8
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PyYAML==5.3.1
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regex==2020年9月27日
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requests==2.24.0
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requests-oauthlib==1.3.0
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six==1.15.0
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textblob==0.15.3
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tqdm==4.50.0
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tweepy==3.9.0
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urllib3==1.25.10
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wcwidth==0.2.5
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xlwt==1.3.0
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import re
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import sys
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import tweepy
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import yaml
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import xlwt
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from tweepy import OAuthHandler
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from textblob import TextBlob
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class TwitterClient(object):
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def __init__(self):
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"""
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Class constructor: Authentication via twitter API keys
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"""
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with open(r'credentials.yaml') as file:
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cred = yaml.load(file, Loader=yaml.FullLoader)
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consumer_key = cred['consumer_key']
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consumer_secret = cred['consumer_secret']
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access_token = cred['access_token']
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access_token_secret = cred['access_token_secret']
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# attempting authentication
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try:
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self.auth = OAuthHandler(consumer_key, consumer_secret)
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self.auth.set_access_token(access_token, access_token_secret)
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self.api = tweepy.API(self.auth)
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except:
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print("Error: Authentication Failed")
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def clean_tweet(self, tweet):
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"""
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Removing links/special characters to clean up tweet
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"""
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return ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t]) | (\w+:\ / \ / \S+) ", " ", tweet).split())
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def get_tweet_sentiment(self, tweet):
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"""
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Classifying tweet as Positive/Negative/Neutral using textblob's sentiment function
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"""
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analysis = TextBlob(self.clean_tweet(tweet))
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if analysis.sentiment.polarity > 0:
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return 'positive'
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elif analysis.sentiment.polarity == 0:
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return 'neutral'
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else:
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return 'negative'
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def get_tweets(self, hashtag):
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"""
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Fetching & parsing 500 tweets based on hashtag
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"""
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all_tweets = []
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search_words = hashtag
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try:
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tweets = tweepy.Cursor(self.api.search,
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q=search_words,
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lang="en",
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result='recent').items(500)
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for tweet in tweets:
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all_tweets.append(tweet.text)
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return all_tweets
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except tweepy.TweepError as e:
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print("Error : " + str(e))
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def main():
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api = TwitterClient()
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hashtag = sys.argv[1]
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all_tweets = api.get_tweets(hashtag)
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#creating dictionary of tweet + sentiment
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wb = xlwt.Workbook(encoding='utf-8')
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style_head = xlwt.easyxf('pattern: fore_colour green; font: colour black, bold True;align: wrap yes; align: horiz center')
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style_rows = xlwt.easyxf('align: wrap yes; align: horiz center')
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sheet = wb.add_sheet('Analysed Tweets')
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sheet.col(0).width = 256 * 50
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sheet.col(1).width = 256 * 20
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sheet.write(0, 0, 'TWEET',style_head)
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sheet.write(0, 1, 'CLASSIFICATION',style_head)
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for i in range(0,len(all_tweets)):
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sheet.write((i+1),0, all_tweets[i],style_rows)
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sheet.write((i+1),1, api.get_tweet_sentiment(all_tweets[i]),style_rows)
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wb.save('Sentiment_Analysis.xls')
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if __name__ == "__main__":
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main()

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