def primary(input_hashtag):
secrets = Oauth_Secrets() #secrets imported from secrets.py
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
N = 50 #Number of Tweets
Tweets = tweepy.Cursor(api.search, q=input_hashtag).items(N)
neg = 0.0
pos = 0.0
neg_count = 0
neutral_count = 0
pos_count = 0
for tweet in Tweets:
# print tweet.text
blob = TextBlob(tweet.text)
print(blob)
if blob.sentiment.polarity < 0: #Negative
neg += blob.sentiment.polarity
neg_count += 1
elif blob.sentiment.polarity == 0: #Neutral
neutral_count += 1
else: #Positive
pos += blob.sentiment.polarity
pos_count += 1
# print "Total tweets",N
# print "Positive ",float(pos_count/N)*100,"%"
# print "Negative ",float(neg_count/N)*100,"%"
# print "Neutral ",float(neutral_count/N)*100,"%"
return [['Sentiment', 'no. of tweets'], ['Positive', pos_count],
['Neutral', neutral_count], ['Negative', neg_count]]
def primary(hashtag):
secrets = Oauth_Secrets()
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
N = 100
tweets = tweepy.Cursor(api.search, q=hashtag).items(N)
neg = 0.0
pos = 0.0
neg_count = 0
pos_count = 0
neutral_count = 0
for tweet in tweets:
blob = TextBlob(tweet.text)
if blob.sentiment.polarity < 0:
neg += blob.sentiment.polarity
neg_count += 1
elif blob.sentiment.polarity > 0:
pos += blob.sentiment.polarity
pos_count += 1
else:
neutral_count += 1
return [['Sentiment', 'no of tweets'], ['Positive', pos_count],
['Negative', neg_count], ['Neutral', neutral_count]]
def analyze(input_word):
secrets = Oauth_Secrets()
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
Num_tweets = 100
Tweets = tweepy.Cursor(api.search, q=input_word).items(Num_tweets)
negative, positive = (0.0, 0.0)
neg_count, pos_count = (0, 0)
neutral_count = 0
for tweet in Tweets:
# print tweet.text
blob = TextBlob(tweet.text)
if blob.sentiment.polarity < 0: #Negative tweets
negative += blob.sentiment.polarity
neg_count += 1
elif blob.sentiment.polarity == 0: #Neutral tweets
neutral_count += 1
else: #Positive tweets
positive += blob.sentiment.polarity
pos_count += 1
return [['Category', 'Tweets crawled'], ['Positive', pos_count],
['Neutral', neutral_count], ['Negative', neg_count]]
def __init__(self, text):
self.text = text
secrets = Oauth_Secrets()
self.auth = tweepy.OAuthHandler(secrets.consumer_key,
secrets.consumer_secret)
self.auth.set_access_token(secrets.access_token,
secrets.access_token_secret)
self.myStreamListener = MyStreamListener()
self.trending = []
""" Virtually private constructor. """
if StreamTweets.__instance is not None:
raise Exception(
"This class is a singleton! Call the instance methods")
else:
StreamTweets.__instance = self
def primary(input_hashtag):
secrets = Oauth_Secrets() #secrets imported from secrets.py
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
N = 1000 #Number of Tweets
Tweets = tweepy.Cursor(api.search, q=input_hashtag).items(N)
# Tweets=tweepy.Cursor(api.search,q=input_hashtag + " -filter:retweets",rpp=5,lang="en", tweet_mode='extended').items(50)
# tweets_list = []
# for tweet in Tweets:
# temp = {}
# temp["text"] = tweet.full_text
# temp["username"] = tweet.user.screen_name
# tweets_list.append(temp)
# print("tweets::::::",tweets_list)
neg = 0.0
pos = 0.0
pos_list = []
nev_list = []
neut_list = []
neg_count = 0
neutral_count = 0
pos_count = 0
# data = pd.DataFrame(data=[[tweet.text,tweet.created_at,tweet.user.screen_name,tweet.user.location,tweet.user.id,tweet.user.created_at,tweet.user.description] for tweet in Tweets],
# columns=['Tweets','date','user','location','id','join_date','profile_description'])
for tweet in Tweets:
tweet_data_dict = {}
tweet_data_dict = {
'text': tweet.text,
'created_at': tweet.created_at,
'screen_name': tweet.user.screen_name,
'user_location': tweet.user.location,
'user_id': tweet.user.id,
'user_created_at': tweet.user.created_at,
'tweet_user_description': tweet.user.description
}
# print(tweet.)
blob = TextBlob(tweet.text)
if blob.sentiment.polarity < 0: #Negative
neg += blob.sentiment.polarity
neg_count += 1
nev_list.append(tweet_data_dict)
elif blob.sentiment.polarity == 0: #Neutral
neutral_count += 1
neut_list.append(tweet_data_dict)
else: #Positive
pos += blob.sentiment.polarity
pos_count += 1
pos_list.append(tweet_data_dict)
print('pos_list', len(pos_list), 'nev_list', len(nev_list), 'neut_list',
len(neut_list))
# print(nev_list)
return [['Sentiment', 'no. of tweets'], ['Positive', pos_count],
['Neutral', neutral_count], ['Negative', neg_count], {
'Positive_list': pos_list
}, {
'Negative_list': nev_list
}, {
'Neutral_list': neut_list
}]
def getdata(input_hashtag):
# input_hashtag = 'obama'
secrets = Oauth_Secrets()
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
N = 100 # number of tweets
# Tweets = api.user_timeline(id=input_hashtag, count=N)
Tweets = tweepy.Cursor(api.search, q=input_hashtag, lang="en").items(N)
# Tweets = api.geo_search(query='Kenya', granularity="country")
# print(Tweets.text[0])
negative = 0.0
positive = 0.0
negative_count = 0
neutral_count = 0
postive_count = 0
tweets_pos = []
tweets_neg = []
tweets_nut = []
general_location = []
time_negative = {}
time_neutral = {}
time_positive = {}
# if len(Tweets) < 1:
# print("no tweets for now")
# else:
# print(Tweets)
for tweet in Tweets:
# print(tweet.created_at)
# print(tweet.user.location)
# print("placeid:%s" % tweet)
# print(tweet.id_str, tweet.coordinates, tweet.geo, tweet.geocode)
# print(tweet.place.country)
general_location.append(tweet.user.location)
blob = TextBlob(tweet.text)
if blob.sentiment.polarity < 0:
negative += blob.sentiment.polarity
negative_count += 1
tweets_neg.append(tweet.text)
time_negative[tweet.created_at] = tweet.text
elif blob.sentiment.polarity == 0:
neutral_count += 1
tweets_nut.append(tweet.text)
time_neutral[tweet.created_at] = tweet.text
else:
positive += blob.sentiment.polarity
postive_count += 1
tweets_pos.append(tweet.text)
time_positive[tweet.created_at] = tweet.text
# post = ("Positive ", float(postive_count/N)*100, "%")
data = {
'Sample': N,
'Topic': input_hashtag,
'Positive': postive_count,
'Neutral': neutral_count,
'Negative': negative_count,
'Nagative_tweets': tweets_neg,
'Neutral_tweets': tweets_nut,
'Postive_tweets': tweets_pos,
'general_location': general_location,
'time_negative': time_negative,
'time_neutral': time_neutral,
'time_positive': time_positive
}
# print(post)
# print(data)
return data
def getdata(input_hashtag):
# input_hashtag = 'obama'
secrets = Oauth_Secrets()
auth = tweepy.OAuthHandler(secrets.consumer_key, secrets.consumer_secret)
auth.set_access_token(secrets.access_token, secrets.access_token_secret)
api = tweepy.API(auth)
# q='input_hashtag -filter:retweets'
N = 1000 # number of tweets
quiz = input_hashtag + ' -filter:retweets'
print(quiz)
# Tweets = api.user_timeline(id=input_hashtag, count=N)
Tweets = tweepy.Cursor(api.search, q=quiz, tweet_mode='extended',
lang="en").items(N)
# Tweets = api.geo_search(query='Kenya', granularity="country")
# print(Tweets.text[0])
negative = 0.0
positive = 0.0
negative_count = 0
neutral_count = 0
postive_count = 0
tweets_pos = []
tweets_neg = []
tweets_nut = []
# general_location = []
# time_negative = {}
# time_neutral = {}
# time_positive = {}
# if len(Tweets) < 1:
# print("no tweets for now")
# else:
# print(Tweets)
# the key for profile image on tweet json is 'profile_image_url'
for tweet in Tweets:
if tweet.place:
# print(tweet)
print("place is:" + str(tweet.place))
# location works for some
print("user profile location is: " + tweet.user.location)
print(tweet.user.screen_name) # to show username
print(tweet.user.profile_image_url) # to show profile image
# location works for some
print('followers are: ' + str(tweet.user.followers_count)) # followers
# number of user favourites
print('user favourites are:' + str(tweet.user.favourites_count))
# number of tweet retweets
print('retweets are: ' + str(tweet.retweet_count))
# number of tweet favourites
print('favs are: ' + str(tweet.favorite_count))
print(tweet.full_text) # tweet itself
# print('retweets are: ' + str(tweet.retweet_count))
# print('favs are: ' + str(tweet.favorite_count))
print('string is ' + str(tweet.id_str)) # tweet id
# print(tweet)
# print(tweet.text)
# print(tweet.created_at)
# print(tweet.user.location)
# print("placeid:%s" % tweet)
# print(tweet.id_str, tweet.coordinates, tweet.geo, tweet.geocode)
# print(tweet.place.country)
avatar = tweet.user.profile_image_url
username = tweet.user.screen_name
followers = tweet.user.followers_count
retweets = tweet.retweet_count
likes = tweet.favorite_count
tweet_id = tweet.id_str
# general_location.append(tweet.user.location)
blob = TextBlob(tweet.full_text)
if blob.sentiment.polarity < 0:
tweet_full = {}
negative += blob.sentiment.polarity
negative_count += 1
# tweets_neg.append(tweet.text)
# order of dictionary matters as that is how items will be ordered on html regardless of what order you call them on html
tweet_full['avatar'] = (avatar)
tweet_full['username'] = (username)
tweet_full['followers'] = (followers)
tweet_full['tweet'] = (tweet.full_text)
tweet_full['tweet_id'] = (tweet_id)
tweet_full['retweets'] = (retweets)
tweet_full['likes'] = (likes)
tweets_neg.append(tweet_full)
# time_negative[tweet.created_at] = tweet.text
elif blob.sentiment.polarity == 0:
tweet_full = {}
neutral_count += 1
# tweets_nut.append(tweet.text)
tweet_full['avatar'] = (avatar)
tweet_full['username'] = (username)
tweet_full['followers'] = (followers)
tweet_full['tweet'] = (tweet.full_text)
tweet_full['tweet_id'] = (tweet_id)
tweet_full['retweets'] = (retweets)
tweet_full['likes'] = (likes)
tweets_nut.append(tweet_full)
# time_neutral[tweet.created_at] = tweet.text
else:
positive += blob.sentiment.polarity
tweet_full = {}
postive_count += 1
# tweets_pos.append(tweet.text)
tweet_full['avatar'] = (avatar)
tweet_full['username'] = (username)
tweet_full['followers'] = (followers)
tweet_full['tweet'] = (tweet.full_text)
tweet_full['tweet_id'] = (tweet_id)
tweet_full['retweets'] = (retweets)
tweet_full['likes'] = (likes)
tweets_pos.append(tweet_full)
# time_positive[tweet.created_at] = tweet.text
else:
print("tweet has no location")
# post = ("Positive ", float(postive_count/N)*100, "%")
data = {
'Sample': N,
'Topic': input_hashtag,
'Positive': postive_count,
'Neutral': neutral_count,
'Negative': negative_count,
'Negative_tweets': tweets_neg,
'Neutral_tweets': tweets_nut,
'Postive_tweets': tweets_pos,
# 'general_location': general_location,
# 'time_negative': time_negative,
# 'time_neutral': time_neutral,
# 'time_positive': time_positive
}
# print(post)
# print(data)
return data