def Extract(self, username, filters, KEY, SECRET):
authentication = tweepy.OAuthHandler(consumer_key, consumer_secret)
authentication.set_access_token(KEY, SECRET)
TwitterAPI = tweepy.API(authentication)
resp = TwitterAPI.user_timeline(screen_name=username, count=200)
tweets = [tweet._json for tweet in resp]
user = tweets[0]['user']
SentAnaly = SentimentAnalyzer()
TempAnaly = TemporalAnalyzer()
MetaAnaly = MetaDataAnalyzer()
NetAnaly = NetworkAnalyzer()
account = pd.Series()
account = account.append(SentAnaly.SentimentAnalysis(tweets))
account = account.append(TempAnaly.TemporalAnalysis(tweets))
account = account.append(MetaAnaly.MetaDataAnalysis(user))
account = account.append(NetAnaly.NetworkAnalysis(user))
DNN = DNNReg()
temp = list()
temp.append(account)
df = pd.DataFrame(temp)
toints = [
'Blanguage', 'BdefaultProfile', 'BdefaultImage',
'BprofileBackgroundImage', 'Bverified', 'Bprotected', 'BgeoEnabled'
]
sentfeat = [
'positiveNum', 'positivePol', 'neutralNum', 'neutralPol',
'negativeNum', 'negativePol', 'average', 'standardDeviation'
]
metafeat = ['screenNameLength', 'screenNameDigits', 'accountNameLength', 'ageDays',
'descriptionLength', 'Blanguage', 'BdefaultProfile', \
'BdefaultImage', 'BprofileBackgroundImage', 'Bverified', 'Bprotected', 'BgeoEnabled']
netfeat = [
'favoritesCount', 'followersCount', 'friendsCount', 'listedCount'
]
tempfeat = ["tweetsPerDay", "tweetsPerMSecPerDay"]
df[toints] = df[toints].astype(int)
Final = DNN.run(df, "twee")
Sent = DNN.run(df[sentfeat], "sent")
Meta = DNN.run(df[metafeat], "meta")
Temporal = DNN.run(df[tempfeat], "temp")
Network = DNN.run(df[netfeat], "net")
Lang = user['lang']
ret = {
'Final': Final,
'Sentiment': Sent,
'Meta': Meta,
'Temporal': Temporal,
'Network': Network,
'Lang': Lang
}
print(ret, end='')
def Extract(self, handle):
USER = TwitterAPI.get_user(handle)
TWEETS = TwitterAPI.user_timeline(screen_name=handle, count=200)
SentAnalyzer = SentimentAnalyzer()
SentimentReport = SentAnalyzer.SentimentAnalysis(TWEETS)
return SentimentReport
