DetectingMisinformation.py

from credentials import API_KEY, API_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET
from nltk.corpus import stopwords
import tweepy
import json
import nltk
from textblob import TextBlob


auth = tweepy.OAuthHandler(API_KEY, API_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
api = tweepy.API(auth)


class listener(tweepy.StreamListener):
    def on_data(self, data):
        collected_tweet = json.loads(data)
        tweetID = collected_tweet["id"]
        if "extended_tweet" in collected_tweet:
            tweet = collected_tweet['extended_tweet']['full_text']
        else:
            tweet = collected_tweet['text']




        sentiment_analysis(tweet, tweetID)


def sentiment_analysis(tweet, tweetID):
    tokens = nltk.word_tokenize(tweet)
    cleaned = [word for word in tokens if word.isalpha()]
    str = ""
    str.join(cleaned)
    print(str)

    polarity = TextBlob(str).sentiment.polarity
    if polarity <=0.25:
        clean_tweets(tweet,tweetID)
    else:
        return


#Step 1 Parse tweet decode what is said
def clean_tweets(tweet, tweetID):

    tokens = nltk.word_tokenize(tweet)
    tokens = [w.lower() for w in tokens]
    cleaned = [word for word in tokens if word.isalpha()]

    stop_words = set(stopwords.words('english'))
    cleaned = [w for w in cleaned if not w in stop_words]
    porter = nltk.PorterStemmer()
    stemmed = [porter.stem(token) for token in cleaned]


    respondToTweet(stemmed, tweetID)


#Step 2 Get what reply



def respondToTweet(stemmed, tweetID):


    if 'symptom' in stemmed:
        responsetweet = "The main symptoms of coronavirus are: high temperature, continuous cough and loss of smell or taste. Find further information at: https://www.nhs.uk/conditions/coronavirus-covid-19/symptoms/#symptoms"
    elif 'conspiracy' in stemmed:
        responsetweet = "There are a number of different conspiracy theories surrounding the vaccines affects on individuals. Find further information disporving these at: https://www.factcheck.org/search/#gsc.tab=0&gsc.q=covid%20vaccine%20effects&gsc.sort="
    elif 'pregnant' in stemmed:
        responsetweet ="There has been no specific reason to believe that the vaccine is not safe for pregnant women. Find further information at: https://www.who.int/news-room/q-a-detail/coronavirus-disease-(covid-19)-vaccines-safety"
    elif 'bill' or 'gates' in stemmed:
        responsetweet = "A number of different conspiracies have been created surrounding Bill gates which are inccorect. Find further information on the goals of the Gates foundation: https://www.factcheck.org/2020/04/conspiracy-theory-misinterprets-goals-of-gates-fou "
    elif 'more' or 'deaths'
    else:
        return


    response(responsetweet, tweetID)



def streamtweets():
    streaming = listener()
    stream = tweepy.Stream(auth=api.auth, listener=streaming, tweet_mode='extended')
    stream.filter(track=['#corna19vaccine'])


#Step 3 respond
def response(responsetweet, tweetID):

    api.update_status(responsetweet, in_reply_to_status_id=tweetID, auto_populate_reply_metadata=True)


if __name__ == "__main__":
    streamtweets()