def __init__(self, queue, gui):
self.sentiment_analysis = SentimentAnalysis()
threading.Thread.__init__(self)
self.queue = queue
self.tweet = ""
self.count = 0
self.gui = gui
self.label = {-1 : 'Negative', 1 : 'Positive', 0 : 'Neutral'}
self.gradient = {
"Positive" : ["#ddf3eb", "#49c5e0", "#2f606b"],
"Negative" : ["#7de235", "#49e083", "#456b2f"],
"Neutral" : ["#e25d35", "#e09249", "#6b522f"]
}
class AnalyseTweet(threading.Thread):
'''
It tries to analyse the tweet contained in queue and after analysing, puts it in gui
'''
def __init__(self, queue, gui):
self.sentiment_analysis = SentimentAnalysis()
threading.Thread.__init__(self)
self.queue = queue
self.tweet = ""
self.count = 0
self.gui = gui
self.label = {-1 : 'Negative', 1 : 'Positive', 0 : 'Neutral'}
self.gradient = {
"Positive" : ["#ddf3eb", "#49c5e0", "#2f606b"],
"Negative" : ["#7de235", "#49e083", "#456b2f"],
"Neutral" : ["#e25d35", "#e09249", "#6b522f"]
}
def parse_tweet(self, tweet):
try:
tweet_json = json.loads(tweet)
for index in tweet_json:
if index == 'text':
self.tweet = repr(tweet_json[index])
self.tweet = self.tweet[2:]
self.tweet = self.tweet[:len(self.tweet)-1]
self.predict_and_add()
except ValueError:
print "Error : ", tweet
return
def predict_and_add(self):
nb, mi, svm, sel = self.sentiment_analysis.predict(self.tweet)
gradNB = self.gradient[self.label[nb]]
gradMI = self.gradient[self.label[mi]]
gradSVM = self.gradient[self.label[svm]]
gradSelf = self.gradient[self.label[sel]]
self.gui.add(self.tweet, "screenname", "picURL", gradNB, gradMI, gradSVM, gradSelf)
#printing tweet and their sentiment
divider = '-' * (180)
width = 10
dict = {}
dict["tweet"] = self.tweet.ljust(100)
dict["naivebayes"] = self.label[nb].ljust(width)
dict["maxint"] = self.label[mi].ljust(width)
dict["svm"] = self.label[svm].ljust(width)
dict["self"] = self.label[sel].ljust(width)
dict["divider"] = divider
print divider
print "%(tweet)s\t %(naivebayes)s %(maxint)s %(svm)s %(self)s" % dict
# print nb, mi, svm, sel
# print self.tweet
def run(self):
while True:
tweet = self.queue.get()
self.parse_tweet(tweet)
self.queue.task_done()
